Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}
## [1] "CPIAUCSL"
## [1] "CPIAUCSL"
## [1] "USREC"
## [1] "UNRATE"
## [1] "PCEPI"
## [1] "CCSA"
## [1] "CCNSA"
## [1] "NPPTTL"
## [1] "U6RATE"
## [1] "PAYNSA"
## [1] "TABSHNO"
## [1] "HNONWPDPI"
## [1] "INDPRO"
## [1] "RRSFS"
## [1] "RSALES"
## [1] "W875RX1"
## [1] "RPI"
## [1] "PCOPPUSDM"
## [1] "NOBL"
## [1] "SCHD"
## [1] "PFF"
## [1] "HPI"
## [1] "GSFTX"
## [1] "LFMIX"
## [1] "LFMCX"
## [1] "LFMAX"
## [1] "LCSIX"
## [1] "BSV"
## [1] "VBIRX"
## [1] "BIV"
## [1] "VFSUX"
## [1] "LTUIX"
## [1] "PTTPX"
## [1] "NERYX"
## [1] "STIGX"
## [1] "HLGAX"
## [1] "FTRGX"
## [1] "THIIX"
## [1] "PTTRX"
## [1] "BFIGX"
## [1] "VTWO"
## [1] "EIFAX"
## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "ASDAX"
## [1] "TRBUX"
## [1] "PRVIX"
## [1] "PRWCX"
## [1] "ADOZX"
## [1] "MERFX"
## [1] "CMNIX"
## [1] "CIHEX"
## [1] "IMPCH"
## [1] "EXPCH"
## [1] "IMPMX"
## [1] "EXPMX"
## [1] "HSN1FNSA"
## [1] "HNFSUSNSA"
## [1] "BUSLOANS"
## [1] "TOTCI"
## [1] "BUSLOANSNSA"
## [1] "REALLNNSA"
## [1] "REALLN"
## [1] "RELACBW027NBOG"
## [1] "RELACBW027SBOG"
## [1] "RREACBM027NBOG"
## [1] "RREACBM027SBOG"
## [1] "RREACBW027SBOG"
## [1] "RREACBW027NBOG"
## [1] "MORTGAGE30US"
## [1] "CONSUMERNSA"
## [1] "TOTLLNSA"
## [1] "DPSACBW027SBOG"
## [1] "DRCLACBS"
## [1] "TOTCINSA"
## [1] "SRPSABSNNCB"
## [1] "ASTLL"
## [1] "FBDILNECA"
## [1] "ASOLAL"
## [1] "ASTMA"
## [1] "ASHMA"
## [1] "ASMRMA"
## [1] "ASCMA"
## [1] "ASFMA"
## [1] "CCLBSHNO"
## [1] "FBDSILQ027S"
## [1] "FBLL"
## [1] "NCBDBIQ027S"
## [1] "DGS10"
## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "TNX"
## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "CLF"
## [1] "DGS30"
## [1] "DGS1"
## [1] "DGS2"
## [1] "TB3MS"
## [1] "DTB3"
## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "IRX"
## [1] "DCOILWTICO"
## [1] "DCOILBRENTEU"
## [1] "NEWORDER"
## [1] "ALTSALES"
## [1] "ICSA"
## [1] "GSPC"
## [1] "FXAIX"
## [1] "FTIHX"
## [1] "MDIZX"
## [1] "DODIX"
## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "RLG"
## [1] "DJI"
## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.
## [1] "STOXX50E"
## [1] "EFA"
## [1] "GDP"
## [1] "FNDEFX"
## [1] "FDEFX"
## [1] "GDPNOW"
## [1] "GDPC1"
## [1] "GDPDEF"
## [1] "VIG"
## [1] "WLRRAL"
## [1] "FEDFUNDS"
## [1] "GPDI"
## [1] "W790RC1Q027SBEA"
## [1] "MZMV"
## [1] "M1"
## [1] "M2"
## [1] "OPHNFB"
## [1] "IPMAN"
## [1] "IWD"
## [1] "GS5"
## [1] "PSAVERT"
## [1] "VIXCLS"
## [1] "VXX"
## [1] "HOUST1F"
## [1] "GFDEBTN"
## [1] "HOUST"
## [1] "MSPUS"
## [1] "UMDMNO"
## [1] "DGORDER"
## [1] "CSUSHPINSA"
## [1] "GFDEGDQ188S"
## [1] "FYFSD"
## [1] "FYFSGDA188S"
## [1] "GDX"
## [1] "XLE"
## [1] "GSG"
## [1] "WALCL"
## [1] "OUTMS"
## [1] "MANEMP"
## [1] "PRS30006163"
## [1] "BAMLC0A3CA"
## [1] "AAA"
## [1] "SOFR"
## [1] "SOFRVOL"
## [1] "SOFR99"
## [1] "SOFR75"
## [1] "SOFR25"
## [1] "SOFR1"
## [1] "OBFR"
## [1] "OBFR99"
## [1] "OBFR75"
## [1] "OBFR25"
## [1] "OBFR1"
## [1] "RPONTSYD"
## [1] "IOER"
## [1] "WRESBAL"
## [1] "EXCSRESNW"
## [1] "ECBASSETS"
## [1] "EUNNGDP"
## [1] "CEU0600000007"
## [1] "CURRENCY"
## [1] "WCURRNS"
## [1] "BOGMBASE"
## [1] "PRS88003193"
## [1] "PPIACO"
## [1] "PCUOMFGOMFG"
## [1] "POPTHM"
## [1] "POPTHM"
## [1] "CLF16OV"
## [1] "LNU01000000"
## [1] "LNU03000000"
## [1] "UNEMPLOY"
## [1] "RSAFS"
## [1] "FRGSHPUSM649NCIS"
## [1] "BOPGTB"
## [1] "TERMCBPER24NS"
## [1] "A065RC1A027NBEA"
## [1] "PI"
## [1] "PCE"
## [1] "A053RC1Q027SBEA"
## [1] "CPROFIT"
## [1] "SPY"
## [1] "MDY"
## [1] "EES"
## [1] "IJR"
## [1] "VGSTX"
## [1] "VFINX"
## [1] "VOE"
## [1] "VOT"
## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "TMFGX"
## [1] "IWM"
## [1] "ONEQ"
## [1] "FSMAX"
## [1] "FXNAX"
## [1] "HAINX"
## [1] "HNACX"
## [1] "VEU"
## [1] "VEIRX"
## [1] "BIL"
## [1] "IVOO"
## [1] "VO"
## [1] "CZA"
## [1] "VYM"
## [1] "ACWI"
## [1] "SLY"
## [1] "QQQ"
## [1] "HYMB"
## [1] "GOLD"
## [1] "BKR"
## [1] "SLB"
## [1] "HAL"
## [1] "IP"
## [1] "PKG"
## [1] "UPS"
## [1] "FDX"
## [1] "T"
## [1] "VZ"

Load up the EIA data

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date
## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...
## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 671274 Columns: 15
## -- Column specification ------------------------------------------------------------------------------------------------
## Delimiter: ","
## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date
## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Downloading GitHub repo RamiKrispin/coronavirus@master
##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\RtmpCibiiW\remotes1e90c1122ad\RamiKrispin-coronavirus-4620449/DESCRIPTION'
## 
  
  
  
-  preparing 'coronavirus': (1.4s)
##    checking DESCRIPTION meta-information ...
  
   checking DESCRIPTION meta-information ... 
  
v  checking DESCRIPTION meta-information
## 
  
  
  
-  checking for LF line-endings in source and make files and shell scripts (344ms)
## 
  
  
  
-  checking for empty or unneeded directories
## 
  
  
  
-  building 'coronavirus_0.3.32.tar.gz'
## 
  
   
## 
## Caught an warning!
## <simpleWarning: package 'coronavirus' is in use and will not be installed>
## `summarise()` has grouped output by 'country'. You can override using the
## `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.symbols)
## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)
## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRVIX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "FXAIX.Volume has zero or negative values. Log series will be zero."
## [1] "FTIHX.Volume has zero or negative values. Log series will be zero."
## [1] "MDIZX.Volume has zero or negative values. Log series will be zero."
## [1] "DODIX.Volume has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "FSMAX.Volume has zero or negative values. Log series will be zero."
## [1] "FXNAX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "HNACX.Volume has zero or negative values. Log series will be zero."
## [1] "VEIRX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."
df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 25.92 compares to a historical mean value over the last decade of 18.62. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

  • S&P 500 Volume, last updated on 2022-04-01, is flat over the last year and negative over the last month.

Unemployment

  • Headline unemployment (U-3) stands at 3.60% (last updated on 2022-03-01) which is near the 1-year average of 4.66% and rising with respect to the low in the last twelve months of 3.60%. Unlikely the rate will drop again.

  • Payrolls (BLS data, NSA) year-over-year stands at 3.87% which is above the 1-year average of 5.22% and falling with respect to the peak, in the last twelve months, of 10.76%.

  • Jobless claims (ICSA data) year-over-year stands at -72.64% (last updated on 2022-03-26) which is in-line with the 1-year average of -70.68% and below the peak, in the last twelve months, of -55.13%.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

  • Real personal income year over year growth stands at 1.23% (last updated on 2022-02-01). This is below the recent peak of 8.44%.

Yield Curve and Bond Market

  • The 10-year to 3-month yield stands at 1.81% (last updated on 2022-03-31). This is above the recent low of 1.14%. The trend is flat over the last year and positive over the last month.

  • Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  
6-Month High
string.symbol string.description
1 CPIAUCSL Consumer Price Index for All Urban Consumers: All Items
4 PCEPI Personal Consumption Expenditures: Chain-type Price Index
7 NPPTTL Total Nonfarm Private Payroll Employment (ADP)
10 TABSHNO Households and nonprofit organizations; total assets, Level
11 HNONWPDPI Household Net Worth, percent Dispsable Income
12 INDPRO Industrial Production Index
14 RSALES Real Retail Sales (DISCONTINUED)
54 HSN1FNSA New One Family Houses Sold: United States (Monthly, NSA)
55 HNFSUSNSA New One Family Houses for Sale in the United States (Monthly, NSA)
56 BUSLOANS Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
58 BUSLOANSNSA Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
59 REALLNNSA Real Estate Loans, All Commercial Banks (Monthly, NSA)
60 REALLN Real Estate Loans, All Commercial Banks (Monthly, SA)
61 RELACBW027NBOG Real Estate Loans, All Commercial Banks (Weekly, NSA)
62 RELACBW027SBOG Real Estate Loans, All Commercial Banks (Weekly, SA)
64 RREACBM027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
65 RREACBW027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
67 MORTGAGE30US 30-Year Fixed Rate Mortgage Average in the United States
69 TOTLLNSA Loans and Leases in Bank Credit, All Commercial Banks
71 DRCLACBS Delinquency Rate on Consumer Loans, All Commercial Banks, SA
72 TOTCINSA Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
73 SRPSABSNNCB Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
74 ASTLL All sectors; total loans; liability, Level (NSA)
75 FBDILNECA Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
76 ASOLAL All sectors; other loans and advances; liability, Level (NSA)
77 ASTMA All sectors; total mortgages; asset, Level (NSA)
78 ASHMA All sectors; home mortgages; asset, Level (NSA)
79 ASMRMA All sectors; multifamily residential mortgages; asset, Level (NSA)
80 ASCMA All sectors; commercial mortgages; asset, Level (NSA)
81 ASFMA All sectors; farm mortgages; asset, Level (NSA)
82 CCLBSHNO Households and nonprofit organizations; consumer credit; liability, Level (NSA)
83 FBDSILQ027S Domestic financial sectors debt securities; liability, Level (NSA)
84 FBLL Domestic financial sectors loans; liability, Level (NSA)
85 NCBDBIQ027S Nonfinancial corporate business; debt securities; liability, Level
92 TB3MS 3-Month Treasury Bill: Secondary Market Rate (Monthly)
109 GDP Gross Domestic Product
110 FNDEFX Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
111 FDEFX Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
113 GDPC1 Real Gross Domestic Product
114 GDPDEF Gross Domestic Product: Implicit Price Deflator
117 FEDFUNDS Effective Federal Funds Rate
118 GPDI Gross Private Domestic Investment
119 W790RC1Q027SBEA Net domestic investment: Private: Domestic busines
120 MZMV Velocity of MZM Money Stock
121 M1 M1 Money Stock
122 M2 M2 Money Stock
123 OPHNFB Nonfarm Business Sector: Real Output Per Hour of All Persons
124 IPMAN Industrial Production: Manufacturing (NAICS)
126 GS5 5-Year Treasury Constant Maturity Rate
131 GFDEBTN Federal Debt: Total Public Debt
132 HOUST Housing Starts: Total: New Privately Owned Housing Units Started
133 MSPUS Median Sales Price of Houses Sold for the United States
136 CSUSHPINSA S&P/Case-Shiller U.S. National Home Price Index (NSA)
137 GFDEGDQ188S Federal Debt: Total Public Debt as Percent of Gross Domestic Product
138 FYFSD Federal Surplus or Deficit
139 FYFSGDA188S Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
144 OUTMS Manufacturing Sector: Real Output
145 MANEMP All Employees: Manufacturing
146 PRS30006163 Manufacturing Sector: Real Output Per Person
148 AAA Moody’s Seasoned Aaa Corporate Bond Yield
151 SOFR99 Secured Overnight Financing Rate: 99th Percentile
152 SOFR75 Secured Overnight Financing Rate: 75th Percentile
155 OBFR Overnight Bank Funding Rate
156 OBFR99 Overnight Bank Funding Rate: 99th Percentile
157 OBFR75 Overnight Bank Funding Rate: 75th Percentile
161 IOER Interest Rate on Excess Reserves
163 EXCSRESNW Excess Reserves of Depository Institutions
164 ECBASSETS Central Bank Assets for Euro Area (11-19 Countries)
165 EUNNGDP Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
167 CURRENCY Currency Component of M1 (Seasonally Adjusted)
168 WCURRNS Currency Component of M1
170 PRS88003193 Nonfinancial Corporations Sector: Unit Profits
171 PPIACO Producer Price Index for All Commodities
172 PCUOMFGOMFG Producer Price Index by Industry: Total Manufacturing Industries
173 POPTHM Population (U.S.)
174 POPTHM Population (U.S.)
175 CLF16OV Civilian Labor Force Level, SA
176 LNU01000000 Civilian Labor Force Level, NSA
179 RSAFS Advance Retail Sales: Retail and Food Services
183 A065RC1A027NBEA Personal income (NSA)
184 PI Personal income (SA)
185 PCE Personal Consumption Expenditures (SA)
186 A053RC1Q027SBEA National income: Corporate profits before tax (without IVA and CCAdj)
187 CPROFIT Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
226 MULTPLSP500SALESQUARTER S&P 500 TTM Sales (Not Inflation Adjusted)
228 MULTPLSP500DIVMONTH S&P 500 Dividend by Month (Inflation Adjusted)
229 CHRISCMEHG1 Copper Futures, Continuous Contract #1 (HG1) (Front Month)
230 WWDIWLDISAIRGOODMTK1 Air transport, freight
232 PETA103600001M U.S. Total Gasoline Retail Sales by Refiners, Monthly
233 PETA123600001M U.S. Regular Gasoline Retail Sales by Refiners, Monthly
234 PETA143B00001M U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
235 PETA133B00001M U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
236 TOTALOGNRPUSM Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
237 TOTALPANRPUSM Crude Oil Rotary Rigs in Operation, Monthly
238 TOTALNGNRPUSM Natural Gas Rotary Rigs in Operation, Monthly
239 BKRTotal Total Rig Count
240 BKRGas Gas Rig Count
241 BKROil Oil Rig Count
242 FARMINCOME Net Farm Income
243 OPEARNINGSPERSHARE Operating Earnings per Share
244 AREARNINGSPERSHARE As-Reported Earnings per Share
245 CASHDIVIDENDSPERSHR Cash Dividends per Share
246 SALESPERSHR Sales per Share
247 BOOKVALPERSHR Book value per Share
248 CAPEXPERSHR Cap ex per Share
249 PRICE Price
250 OPEARNINGSTTM TTM Operating Earnings
251 AREARNINGSTTM TTM Reported Earnings
252 FINRAMarginDebt Margin Debt
253 FINRAFreeCreditMargin Free Credit Balances in Customers’ Securities Margin Accounts
254 OCCEquityVolume Equity Options Volume
255 OCCNonEquityVolume Non-Equity Options Volume
259 BUSLOANS.by.GDP Business Loans Normalized by GDP
262 BUSLOANSNSA.by.GDP Business Loans Normalized by GDP
264 TOTCINSA.by.GDP Business Loans (Weekly, NSA) Normalized by GDP
268 A065RC1A027NBEA.by.GDP Personal Income (NSA) Normalized by GDP
269 PI.by.GDP Personal Income (SA) Normalized by GDP
270 A053RC1Q027SBEA.by.GDP National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
271 CPROFIT.by.GDP National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
274 RREACBM027SBOG.by.GDP Residental Real Estate Loans (Monthly, SA) divided by GDP
275 RREACBW027SBOG.by.GDP Residental Real Estate Loans (Weekly, SA) divided by GDP
279 ASHMA.by.GDP Home Mortgages (Quarterly, NSA) divided by GDP
280 ASHMA.INTEREST Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
284 TOTLNNSA Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
285 TOTLNNSA.by.GDP Total Loans Not Seasonally Adjusted divided by GDP
289 EXCSRESNW.by.GDP Excess Reserves of Depository Institutions Divided by GDP
294 SRPSABSNNCB.by.GDP Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
295 ASTLL.by.GDP All sectors; total loans; liability, Level (NSA) Divided by GDP
296 ASFMA.by.GDP All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
297 ASFMA.by.ASTLL All sectors; total loans Divided by farm mortgages
298 ASFMA.INTEREST Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
299 ASFMA.INTEREST.by.GDP Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
300 FARMINCOME.by.GDP Farm Income (Annual, NSA) Divided by GDP
303 ECBASSETS.by.EUNNGDP Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
312 NPPTTLBYPOPTHM ADP Private Employment / Population
332 MSPUS.times.HOUST New privately owned units start times median price
333 MSPUS.times.HNFSUSNSA New privately owned 1-family units for sale times median price
337 CPIAUCSL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Price Index for All Urban Consumers: All Items
340 CPIAUCSL_Log Log of Consumer Price Index for All Urban Consumers: All Items
341 CPIAUCSL_mva200 Consumer Price Index for All Urban Consumers: All Items 200 Day MA
342 CPIAUCSL_mva050 Consumer Price Index for All Urban Consumers: All Items 50 Day MA
343 USREC_YoY NBER based Recession Indicators Year over Year
344 USREC_YoY4 NBER based Recession Indicators 4 Year over 4 Year
345 USREC_YoY5 NBER based Recession Indicators 5 Year over 5 Year
346 USREC_Smooth Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
347 USREC_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
348 USREC_SmoothDer Derivative of Smoothed NBER based Recession Indicators
349 USREC_Log Log of NBER based Recession Indicators
350 USREC_mva200 NBER based Recession Indicators 200 Day MA
351 USREC_mva050 NBER based Recession Indicators 50 Day MA
357 UNRATE_SmoothDer Derivative of Smoothed Civilian Unemployment Rate U-3
364 PCEPI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures: Chain-type Price Index
367 PCEPI_Log Log of Personal Consumption Expenditures: Chain-type Price Index
368 PCEPI_mva200 Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
369 PCEPI_mva050 Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
379 CCNSA_YoY Continued Claims (Insured Unemployment, NSA) Year over Year
384 CCNSA_SmoothDer Derivative of Smoothed Continued Claims (Insured Unemployment, NSA)
391 NPPTTL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Nonfarm Private Payroll Employment (ADP)
393 NPPTTL_SmoothDer Derivative of Smoothed Total Nonfarm Private Payroll Employment (ADP)
394 NPPTTL_Log Log of Total Nonfarm Private Payroll Employment (ADP)
395 NPPTTL_mva200 Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
396 NPPTTL_mva050 Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
402 U6RATE_SmoothDer Derivative of Smoothed Total unemployed + margin + part-time U-6
413 PAYNSA_mva200 All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
421 TABSHNO_Log Log of Households and nonprofit organizations; total assets, Level
422 TABSHNO_mva200 Households and nonprofit organizations; total assets, Level 200 Day MA
423 TABSHNO_mva050 Households and nonprofit organizations; total assets, Level 50 Day MA
430 HNONWPDPI_Log Log of Household Net Worth, percent Dispsable Income
431 HNONWPDPI_mva200 Household Net Worth, percent Dispsable Income 200 Day MA
432 HNONWPDPI_mva050 Household Net Worth, percent Dispsable Income 50 Day MA
436 INDPRO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Industrial Production Index
438 INDPRO_SmoothDer Derivative of Smoothed Industrial Production Index
439 INDPRO_Log Log of Industrial Production Index
440 INDPRO_mva200 Industrial Production Index 200 Day MA
441 INDPRO_mva050 Industrial Production Index 50 Day MA
445 RRSFS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Retail and Food Services Sales
447 RRSFS_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales
449 RRSFS_mva200 Real Retail and Food Services Sales 200 Day MA
451 RSALES_YoY Real Retail Sales (DISCONTINUED) Year over Year
452 RSALES_YoY4 Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
453 RSALES_YoY5 Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
457 RSALES_Log Log of Real Retail Sales (DISCONTINUED)
458 RSALES_mva200 Real Retail Sales (DISCONTINUED) 200 Day MA
459 RSALES_mva050 Real Retail Sales (DISCONTINUED) 50 Day MA
474 RPI_SmoothDer Derivative of Smoothed Real personal income
483 PCOPPUSDM_SmoothDer Derivative of Smoothed Global price of Copper
485 PCOPPUSDM_mva200 Global price of Copper 200 Day MA
526 NOBL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
528 NOBL.Volume_SmoothDer Derivative of Smoothed
530 NOBL.Volume_mva200 200 Day MA
548 SCHD.Open_mva200 200 Day MA
557 SCHD.High_mva200 200 Day MA
566 SCHD.Low_mva200 200 Day MA
575 SCHD.Close_mva200 200 Day MA
580 SCHD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
582 SCHD.Volume_SmoothDer Derivative of Smoothed
584 SCHD.Volume_mva200 200 Day MA
593 SCHD.Adjusted_mva200 200 Day MA
636 PFF.Volume_SmoothDer Derivative of Smoothed
638 PFF.Volume_mva200 200 Day MA
688 HPI.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
690 HPI.Volume_SmoothDer Derivative of Smoothed
692 HPI.Volume_mva200 200 Day MA
739 GSFTX.Volume_YoY Year over Year
740 GSFTX.Volume_YoY4 4 Year over 4 Year
741 GSFTX.Volume_YoY5 5 Year over 5 Year
742 GSFTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
743 GSFTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
744 GSFTX.Volume_SmoothDer Derivative of Smoothed
745 GSFTX.Volume_Log Log of
746 GSFTX.Volume_mva200 200 Day MA
747 GSFTX.Volume_mva050 50 Day MA
755 GSFTX.Adjusted_mva200 200 Day MA
760 LFMIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
762 LFMIX.Open_SmoothDer Derivative of Smoothed
769 LFMIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
771 LFMIX.High_SmoothDer Derivative of Smoothed
778 LFMIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
780 LFMIX.Low_SmoothDer Derivative of Smoothed
787 LFMIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
789 LFMIX.Close_SmoothDer Derivative of Smoothed
793 LFMIX.Volume_YoY Year over Year
794 LFMIX.Volume_YoY4 4 Year over 4 Year
795 LFMIX.Volume_YoY5 5 Year over 5 Year
796 LFMIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
797 LFMIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
798 LFMIX.Volume_SmoothDer Derivative of Smoothed
799 LFMIX.Volume_Log Log of
800 LFMIX.Volume_mva200 200 Day MA
801 LFMIX.Volume_mva050 50 Day MA
805 LFMIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
807 LFMIX.Adjusted_SmoothDer Derivative of Smoothed
810 LFMIX.Adjusted_mva050 50 Day MA
814 LFMCX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
816 LFMCX.Open_SmoothDer Derivative of Smoothed
823 LFMCX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
825 LFMCX.High_SmoothDer Derivative of Smoothed
832 LFMCX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
834 LFMCX.Low_SmoothDer Derivative of Smoothed
841 LFMCX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
843 LFMCX.Close_SmoothDer Derivative of Smoothed
847 LFMCX.Volume_YoY Year over Year
848 LFMCX.Volume_YoY4 4 Year over 4 Year
849 LFMCX.Volume_YoY5 5 Year over 5 Year
850 LFMCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
851 LFMCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
852 LFMCX.Volume_SmoothDer Derivative of Smoothed
853 LFMCX.Volume_Log Log of
854 LFMCX.Volume_mva200 200 Day MA
855 LFMCX.Volume_mva050 50 Day MA
859 LFMCX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
861 LFMCX.Adjusted_SmoothDer Derivative of Smoothed
864 LFMCX.Adjusted_mva050 50 Day MA
868 LFMAX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
870 LFMAX.Open_SmoothDer Derivative of Smoothed
877 LFMAX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
879 LFMAX.High_SmoothDer Derivative of Smoothed
886 LFMAX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
888 LFMAX.Low_SmoothDer Derivative of Smoothed
895 LFMAX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
897 LFMAX.Close_SmoothDer Derivative of Smoothed
901 LFMAX.Volume_YoY Year over Year
902 LFMAX.Volume_YoY4 4 Year over 4 Year
903 LFMAX.Volume_YoY5 5 Year over 5 Year
904 LFMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
905 LFMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
906 LFMAX.Volume_SmoothDer Derivative of Smoothed
907 LFMAX.Volume_Log Log of
908 LFMAX.Volume_mva200 200 Day MA
909 LFMAX.Volume_mva050 50 Day MA
913 LFMAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
915 LFMAX.Adjusted_SmoothDer Derivative of Smoothed
918 LFMAX.Adjusted_mva050 50 Day MA
922 LCSIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
926 LCSIX.Open_mva200 200 Day MA
931 LCSIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
935 LCSIX.High_mva200 200 Day MA
940 LCSIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
944 LCSIX.Low_mva200 200 Day MA
949 LCSIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
953 LCSIX.Close_mva200 200 Day MA
955 LCSIX.Volume_YoY Year over Year
956 LCSIX.Volume_YoY4 4 Year over 4 Year
957 LCSIX.Volume_YoY5 5 Year over 5 Year
958 LCSIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
959 LCSIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
960 LCSIX.Volume_SmoothDer Derivative of Smoothed
961 LCSIX.Volume_Log Log of
962 LCSIX.Volume_mva200 200 Day MA
963 LCSIX.Volume_mva050 50 Day MA
967 LCSIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
969 LCSIX.Adjusted_SmoothDer Derivative of Smoothed
971 LCSIX.Adjusted_mva200 200 Day MA
972 LCSIX.Adjusted_mva050 50 Day MA
1012 BSV.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1014 BSV.Volume_SmoothDer Derivative of Smoothed
1016 BSV.Volume_mva200 200 Day MA
1063 VBIRX.Volume_YoY Year over Year
1064 VBIRX.Volume_YoY4 4 Year over 4 Year
1065 VBIRX.Volume_YoY5 5 Year over 5 Year
1066 VBIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1067 VBIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1068 VBIRX.Volume_SmoothDer Derivative of Smoothed
1069 VBIRX.Volume_Log Log of
1070 VBIRX.Volume_mva200 200 Day MA
1071 VBIRX.Volume_mva050 50 Day MA
1120 BIV.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1122 BIV.Volume_SmoothDer Derivative of Smoothed
1171 VFSUX.Volume_YoY Year over Year
1172 VFSUX.Volume_YoY4 4 Year over 4 Year
1173 VFSUX.Volume_YoY5 5 Year over 5 Year
1174 VFSUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1175 VFSUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1176 VFSUX.Volume_SmoothDer Derivative of Smoothed
1177 VFSUX.Volume_Log Log of
1178 VFSUX.Volume_mva200 200 Day MA
1179 VFSUX.Volume_mva050 50 Day MA
1225 LTUIX.Volume_YoY Year over Year
1226 LTUIX.Volume_YoY4 4 Year over 4 Year
1227 LTUIX.Volume_YoY5 5 Year over 5 Year
1228 LTUIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1229 LTUIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1230 LTUIX.Volume_SmoothDer Derivative of Smoothed
1231 LTUIX.Volume_Log Log of
1232 LTUIX.Volume_mva200 200 Day MA
1233 LTUIX.Volume_mva050 50 Day MA
1279 PTTPX.Volume_YoY Year over Year
1280 PTTPX.Volume_YoY4 4 Year over 4 Year
1281 PTTPX.Volume_YoY5 5 Year over 5 Year
1282 PTTPX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1283 PTTPX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1284 PTTPX.Volume_SmoothDer Derivative of Smoothed
1285 PTTPX.Volume_Log Log of
1286 PTTPX.Volume_mva200 200 Day MA
1287 PTTPX.Volume_mva050 50 Day MA
1333 NERYX.Volume_YoY Year over Year
1334 NERYX.Volume_YoY4 4 Year over 4 Year
1335 NERYX.Volume_YoY5 5 Year over 5 Year
1336 NERYX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1337 NERYX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1338 NERYX.Volume_SmoothDer Derivative of Smoothed
1339 NERYX.Volume_Log Log of
1340 NERYX.Volume_mva200 200 Day MA
1341 NERYX.Volume_mva050 50 Day MA
1387 STIGX.Volume_YoY Year over Year
1388 STIGX.Volume_YoY4 4 Year over 4 Year
1389 STIGX.Volume_YoY5 5 Year over 5 Year
1390 STIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1391 STIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1392 STIGX.Volume_SmoothDer Derivative of Smoothed
1393 STIGX.Volume_Log Log of
1394 STIGX.Volume_mva200 200 Day MA
1395 STIGX.Volume_mva050 50 Day MA
1441 HLGAX.Volume_YoY Year over Year
1442 HLGAX.Volume_YoY4 4 Year over 4 Year
1443 HLGAX.Volume_YoY5 5 Year over 5 Year
1444 HLGAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1445 HLGAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1446 HLGAX.Volume_SmoothDer Derivative of Smoothed
1447 HLGAX.Volume_Log Log of
1448 HLGAX.Volume_mva200 200 Day MA
1449 HLGAX.Volume_mva050 50 Day MA
1495 FTRGX.Volume_YoY Year over Year
1496 FTRGX.Volume_YoY4 4 Year over 4 Year
1497 FTRGX.Volume_YoY5 5 Year over 5 Year
1498 FTRGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1499 FTRGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1500 FTRGX.Volume_SmoothDer Derivative of Smoothed
1501 FTRGX.Volume_Log Log of
1502 FTRGX.Volume_mva200 200 Day MA
1503 FTRGX.Volume_mva050 50 Day MA
1549 THIIX.Volume_YoY Year over Year
1550 THIIX.Volume_YoY4 4 Year over 4 Year
1551 THIIX.Volume_YoY5 5 Year over 5 Year
1552 THIIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1553 THIIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1554 THIIX.Volume_SmoothDer Derivative of Smoothed
1555 THIIX.Volume_Log Log of
1556 THIIX.Volume_mva200 200 Day MA
1557 THIIX.Volume_mva050 50 Day MA
1603 PTTRX.Volume_YoY Year over Year
1604 PTTRX.Volume_YoY4 4 Year over 4 Year
1605 PTTRX.Volume_YoY5 5 Year over 5 Year
1606 PTTRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1607 PTTRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1608 PTTRX.Volume_SmoothDer Derivative of Smoothed
1609 PTTRX.Volume_Log Log of
1610 PTTRX.Volume_mva200 200 Day MA
1611 PTTRX.Volume_mva050 50 Day MA
1657 BFIGX.Volume_YoY Year over Year
1658 BFIGX.Volume_YoY4 4 Year over 4 Year
1659 BFIGX.Volume_YoY5 5 Year over 5 Year
1660 BFIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1661 BFIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1662 BFIGX.Volume_SmoothDer Derivative of Smoothed
1663 BFIGX.Volume_Log Log of
1664 BFIGX.Volume_mva200 200 Day MA
1665 BFIGX.Volume_mva050 50 Day MA
1718 VTWO.Volume_mva200 200 Day MA
1765 EIFAX.Volume_YoY Year over Year
1766 EIFAX.Volume_YoY4 4 Year over 4 Year
1767 EIFAX.Volume_YoY5 5 Year over 5 Year
1768 EIFAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1769 EIFAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1770 EIFAX.Volume_SmoothDer Derivative of Smoothed
1771 EIFAX.Volume_Log Log of
1772 EIFAX.Volume_mva200 200 Day MA
1773 EIFAX.Volume_mva050 50 Day MA
1819 ASDAX.Volume_YoY Year over Year
1820 ASDAX.Volume_YoY4 4 Year over 4 Year
1821 ASDAX.Volume_YoY5 5 Year over 5 Year
1822 ASDAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1823 ASDAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1824 ASDAX.Volume_SmoothDer Derivative of Smoothed
1825 ASDAX.Volume_Log Log of
1826 ASDAX.Volume_mva200 200 Day MA
1827 ASDAX.Volume_mva050 50 Day MA
1873 TRBUX.Volume_YoY Year over Year
1874 TRBUX.Volume_YoY4 4 Year over 4 Year
1875 TRBUX.Volume_YoY5 5 Year over 5 Year
1876 TRBUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1877 TRBUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1878 TRBUX.Volume_SmoothDer Derivative of Smoothed
1879 TRBUX.Volume_Log Log of
1880 TRBUX.Volume_mva200 200 Day MA
1881 TRBUX.Volume_mva050 50 Day MA
1927 PRVIX.Volume_YoY Year over Year
1928 PRVIX.Volume_YoY4 4 Year over 4 Year
1929 PRVIX.Volume_YoY5 5 Year over 5 Year
1930 PRVIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1931 PRVIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1932 PRVIX.Volume_SmoothDer Derivative of Smoothed
1933 PRVIX.Volume_Log Log of
1934 PRVIX.Volume_mva200 200 Day MA
1935 PRVIX.Volume_mva050 50 Day MA
1981 PRWCX.Volume_YoY Year over Year
1982 PRWCX.Volume_YoY4 4 Year over 4 Year
1983 PRWCX.Volume_YoY5 5 Year over 5 Year
1984 PRWCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1985 PRWCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1986 PRWCX.Volume_SmoothDer Derivative of Smoothed
1987 PRWCX.Volume_Log Log of
1988 PRWCX.Volume_mva200 200 Day MA
1989 PRWCX.Volume_mva050 50 Day MA
2035 ADOZX.Volume_YoY Year over Year
2036 ADOZX.Volume_YoY4 4 Year over 4 Year
2037 ADOZX.Volume_YoY5 5 Year over 5 Year
2038 ADOZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2039 ADOZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2040 ADOZX.Volume_SmoothDer Derivative of Smoothed
2041 ADOZX.Volume_Log Log of
2042 ADOZX.Volume_mva200 200 Day MA
2043 ADOZX.Volume_mva050 50 Day MA
2056 MERFX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2058 MERFX.Open_SmoothDer Derivative of Smoothed
2065 MERFX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2067 MERFX.High_SmoothDer Derivative of Smoothed
2074 MERFX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2076 MERFX.Low_SmoothDer Derivative of Smoothed
2083 MERFX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2085 MERFX.Close_SmoothDer Derivative of Smoothed
2089 MERFX.Volume_YoY Year over Year
2090 MERFX.Volume_YoY4 4 Year over 4 Year
2091 MERFX.Volume_YoY5 5 Year over 5 Year
2092 MERFX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2093 MERFX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2094 MERFX.Volume_SmoothDer Derivative of Smoothed
2095 MERFX.Volume_Log Log of
2096 MERFX.Volume_mva200 200 Day MA
2097 MERFX.Volume_mva050 50 Day MA
2101 MERFX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2102 MERFX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2103 MERFX.Adjusted_SmoothDer Derivative of Smoothed
2104 MERFX.Adjusted_Log Log of
2106 MERFX.Adjusted_mva050 50 Day MA
2143 CMNIX.Volume_YoY Year over Year
2144 CMNIX.Volume_YoY4 4 Year over 4 Year
2145 CMNIX.Volume_YoY5 5 Year over 5 Year
2146 CMNIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2147 CMNIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2148 CMNIX.Volume_SmoothDer Derivative of Smoothed
2149 CMNIX.Volume_Log Log of
2150 CMNIX.Volume_mva200 200 Day MA
2151 CMNIX.Volume_mva050 50 Day MA
2197 CIHEX.Volume_YoY Year over Year
2198 CIHEX.Volume_YoY4 4 Year over 4 Year
2199 CIHEX.Volume_YoY5 5 Year over 5 Year
2200 CIHEX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2201 CIHEX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2202 CIHEX.Volume_SmoothDer Derivative of Smoothed
2203 CIHEX.Volume_Log Log of
2204 CIHEX.Volume_mva200 200 Day MA
2205 CIHEX.Volume_mva050 50 Day MA
2222 IMPCH_mva200 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 200 Day MA
2240 IMPMX_mva200 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 200 Day MA
2247 EXPMX_SmoothDer Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2254 HSN1FNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses Sold: United States (Monthly, NSA)
2256 HSN1FNSA_SmoothDer Derivative of Smoothed New One Family Houses Sold: United States (Monthly, NSA)
2257 HSN1FNSA_Log Log of New One Family Houses Sold: United States (Monthly, NSA)
2259 HSN1FNSA_mva050 New One Family Houses Sold: United States (Monthly, NSA) 50 Day MA
2263 HNFSUSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses for Sale in the United States (Monthly, NSA)
2266 HNFSUSNSA_Log Log of New One Family Houses for Sale in the United States (Monthly, NSA)
2267 HNFSUSNSA_mva200 New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2268 HNFSUSNSA_mva050 New One Family Houses for Sale in the United States (Monthly, NSA) 50 Day MA
2269 BUSLOANS_YoY Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) Year over Year
2274 BUSLOANS_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2275 BUSLOANS_Log Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2277 BUSLOANS_mva050 Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2281 TOTCI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2283 TOTCI_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2286 TOTCI_mva050 Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2292 BUSLOANSNSA_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2293 BUSLOANSNSA_Log Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2295 BUSLOANSNSA_mva050 Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2302 REALLNNSA_Log Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2303 REALLNNSA_mva200 Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2304 REALLNNSA_mva050 Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2311 REALLN_Log Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2312 REALLN_mva200 Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2313 REALLN_mva050 Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2317 RELACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, NSA)
2320 RELACBW027NBOG_Log Log of Real Estate Loans, All Commercial Banks (Weekly, NSA)
2321 RELACBW027NBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2322 RELACBW027NBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2326 RELACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2328 RELACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, SA)
2329 RELACBW027SBOG_Log Log of Real Estate Loans, All Commercial Banks (Weekly, SA)
2330 RELACBW027SBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2331 RELACBW027SBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2332 RREACBM027NBOG_YoY Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) Year over Year
2339 RREACBM027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2341 RREACBM027SBOG_YoY Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) Year over Year
2347 RREACBM027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2348 RREACBM027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2349 RREACBM027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2353 RREACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2355 RREACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2356 RREACBW027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2357 RREACBW027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2358 RREACBW027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2366 RREACBW027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2367 RREACBW027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2369 MORTGAGE30US_YoY4 30-Year Fixed Rate Mortgage Average in the United States 4 Year over 4 Year
2370 MORTGAGE30US_YoY5 30-Year Fixed Rate Mortgage Average in the United States 5 Year over 5 Year
2371 MORTGAGE30US_Smooth Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2372 MORTGAGE30US_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 30-Year Fixed Rate Mortgage Average in the United States
2373 MORTGAGE30US_SmoothDer Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2374 MORTGAGE30US_Log Log of 30-Year Fixed Rate Mortgage Average in the United States
2375 MORTGAGE30US_mva200 30-Year Fixed Rate Mortgage Average in the United States 200 Day MA
2376 MORTGAGE30US_mva050 30-Year Fixed Rate Mortgage Average in the United States 50 Day MA
2384 CONSUMERNSA_mva200 Consumer Loans, All Commercial Banks 200 Day MA
2389 TOTLLNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2391 TOTLLNSA_SmoothDer Derivative of Smoothed Loans and Leases in Bank Credit, All Commercial Banks
2392 TOTLLNSA_Log Log of Loans and Leases in Bank Credit, All Commercial Banks
2393 TOTLLNSA_mva200 Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2394 TOTLLNSA_mva050 Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2398 DPSACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Deposits, All Commercial Banks
2402 DPSACBW027SBOG_mva200 Deposits, All Commercial Banks 200 Day MA
2403 DPSACBW027SBOG_mva050 Deposits, All Commercial Banks 50 Day MA
2404 DRCLACBS_YoY Delinquency Rate on Consumer Loans, All Commercial Banks, SA Year over Year
2410 DRCLACBS_Log Log of Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2411 DRCLACBS_mva200 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 200 Day MA
2412 DRCLACBS_mva050 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 50 Day MA
2413 TOTCINSA_YoY Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) Year over Year
2416 TOTCINSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2418 TOTCINSA_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2419 TOTCINSA_Log Log of Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2421 TOTCINSA_mva050 Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2423 SRPSABSNNCB_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 4 Year over 4 Year
2424 SRPSABSNNCB_YoY5 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 5 Year over 5 Year
2427 SRPSABSNNCB_SmoothDer Derivative of Smoothed Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2428 SRPSABSNNCB_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2429 SRPSABSNNCB_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 200 Day MA
2430 SRPSABSNNCB_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 50 Day MA
2437 ASTLL_Log Log of All sectors; total loans; liability, Level (NSA)
2438 ASTLL_mva200 All sectors; total loans; liability, Level (NSA) 200 Day MA
2439 ASTLL_mva050 All sectors; total loans; liability, Level (NSA) 50 Day MA
2440 FBDILNECA_YoY Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) Year over Year
2446 FBDILNECA_Log Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2447 FBDILNECA_mva200 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 200 Day MA
2448 FBDILNECA_mva050 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 50 Day MA
2452 ASOLAL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; other loans and advances; liability, Level (NSA)
2455 ASOLAL_Log Log of All sectors; other loans and advances; liability, Level (NSA)
2456 ASOLAL_mva200 All sectors; other loans and advances; liability, Level (NSA) 200 Day MA
2457 ASOLAL_mva050 All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2464 ASTMA_Log Log of All sectors; total mortgages; asset, Level (NSA)
2465 ASTMA_mva200 All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2466 ASTMA_mva050 All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2473 ASHMA_Log Log of All sectors; home mortgages; asset, Level (NSA)
2474 ASHMA_mva200 All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2475 ASHMA_mva050 All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2482 ASMRMA_Log Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2483 ASMRMA_mva200 All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2484 ASMRMA_mva050 All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2491 ASCMA_Log Log of All sectors; commercial mortgages; asset, Level (NSA)
2492 ASCMA_mva200 All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2493 ASCMA_mva050 All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2500 ASFMA_Log Log of All sectors; farm mortgages; asset, Level (NSA)
2501 ASFMA_mva200 All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2502 ASFMA_mva050 All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2509 CCLBSHNO_Log Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2510 CCLBSHNO_mva200 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 200 Day MA
2511 CCLBSHNO_mva050 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 50 Day MA
2518 FBDSILQ027S_Log Log of Domestic financial sectors debt securities; liability, Level (NSA)
2519 FBDSILQ027S_mva200 Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2520 FBDSILQ027S_mva050 Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2527 FBLL_Log Log of Domestic financial sectors loans; liability, Level (NSA)
2528 FBLL_mva200 Domestic financial sectors loans; liability, Level (NSA) 200 Day MA
2529 FBLL_mva050 Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2533 NCBDBIQ027S_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; debt securities; liability, Level
2536 NCBDBIQ027S_Log Log of Nonfinancial corporate business; debt securities; liability, Level
2542 DGS10_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2544 DGS10_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2546 DGS10_mva200 10-Year Treasury Constant Maturity Rate 200 Day MA
2547 DGS10_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2551 TNX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2553 TNX.Open_SmoothDer Derivative of Smoothed
2555 TNX.Open_mva200 200 Day MA
2556 TNX.Open_mva050 50 Day MA
2560 TNX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2562 TNX.High_SmoothDer Derivative of Smoothed
2564 TNX.High_mva200 200 Day MA
2565 TNX.High_mva050 50 Day MA
2569 TNX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2571 TNX.Low_SmoothDer Derivative of Smoothed
2573 TNX.Low_mva200 200 Day MA
2574 TNX.Low_mva050 50 Day MA
2578 TNX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2580 TNX.Close_SmoothDer Derivative of Smoothed
2582 TNX.Close_mva200 200 Day MA
2583 TNX.Close_mva050 50 Day MA
2584 TNX.Volume_YoY Year over Year
2585 TNX.Volume_YoY4 4 Year over 4 Year
2586 TNX.Volume_YoY5 5 Year over 5 Year
2587 TNX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2588 TNX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2589 TNX.Volume_SmoothDer Derivative of Smoothed
2590 TNX.Volume_Log Log of
2591 TNX.Volume_mva200 200 Day MA
2592 TNX.Volume_mva050 50 Day MA
2596 TNX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2598 TNX.Adjusted_SmoothDer Derivative of Smoothed
2600 TNX.Adjusted_mva200 200 Day MA
2601 TNX.Adjusted_mva050 50 Day MA
2605 CLF.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2607 CLF.Open_SmoothDer Derivative of Smoothed
2608 CLF.Open_Log Log of
2609 CLF.Open_mva200 200 Day MA
2610 CLF.Open_mva050 50 Day MA
2614 CLF.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2616 CLF.High_SmoothDer Derivative of Smoothed
2618 CLF.High_mva200 200 Day MA
2619 CLF.High_mva050 50 Day MA
2623 CLF.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2625 CLF.Low_SmoothDer Derivative of Smoothed
2626 CLF.Low_Log Log of
2627 CLF.Low_mva200 200 Day MA
2628 CLF.Low_mva050 50 Day MA
2632 CLF.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2634 CLF.Close_SmoothDer Derivative of Smoothed
2635 CLF.Close_Log Log of
2636 CLF.Close_mva200 200 Day MA
2637 CLF.Close_mva050 50 Day MA
2643 CLF.Volume_SmoothDer Derivative of Smoothed
2644 CLF.Volume_Log Log of
2650 CLF.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2652 CLF.Adjusted_SmoothDer Derivative of Smoothed
2653 CLF.Adjusted_Log Log of
2654 CLF.Adjusted_mva200 200 Day MA
2655 CLF.Adjusted_mva050 50 Day MA
2659 DGS30_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2661 DGS30_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2664 DGS30_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2668 DGS1_Smooth Savitsky-Golay Smoothed (p=3, n=365) 1-Year Treasury Constant Maturity Rate
2670 DGS1_SmoothDer Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2672 DGS1_mva200 1-Year Treasury Constant Maturity Rate 200 Day MA
2673 DGS1_mva050 1-Year Treasury Constant Maturity Rate 50 Day MA
2677 DGS2_Smooth Savitsky-Golay Smoothed (p=3, n=365) 2-Year Treasury Constant Maturity Rate
2679 DGS2_SmoothDer Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2681 DGS2_mva200 2-Year Treasury Constant Maturity Rate 200 Day MA
2682 DGS2_mva050 2-Year Treasury Constant Maturity Rate 50 Day MA
2683 TB3MS_YoY 3-Month Treasury Bill: Secondary Market Rate (Monthly) Year over Year
2686 TB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2688 TB3MS_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2689 TB3MS_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2690 TB3MS_mva200 3-Month Treasury Bill: Secondary Market Rate (Monthly) 200 Day MA
2691 TB3MS_mva050 3-Month Treasury Bill: Secondary Market Rate (Monthly) 50 Day MA
2695 DTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2697 DTB3_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Daily)
2698 DTB3_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2699 DTB3_mva200 3-Month Treasury Bill: Secondary Market Rate (Daily) 200 Day MA
2700 DTB3_mva050 3-Month Treasury Bill: Secondary Market Rate (Daily) 50 Day MA
2704 IRX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2706 IRX.Open_SmoothDer Derivative of Smoothed
2707 IRX.Open_Log Log of
2709 IRX.Open_mva050 50 Day MA
2713 IRX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2715 IRX.High_SmoothDer Derivative of Smoothed
2716 IRX.High_Log Log of
2718 IRX.High_mva050 50 Day MA
2722 IRX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2724 IRX.Low_SmoothDer Derivative of Smoothed
2725 IRX.Low_Log Log of
2726 IRX.Low_mva200 200 Day MA
2727 IRX.Low_mva050 50 Day MA
2731 IRX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2733 IRX.Close_SmoothDer Derivative of Smoothed
2734 IRX.Close_Log Log of
2735 IRX.Close_mva200 200 Day MA
2736 IRX.Close_mva050 50 Day MA
2737 IRX.Volume_YoY Year over Year
2738 IRX.Volume_YoY4 4 Year over 4 Year
2739 IRX.Volume_YoY5 5 Year over 5 Year
2740 IRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2741 IRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2742 IRX.Volume_SmoothDer Derivative of Smoothed
2743 IRX.Volume_Log Log of
2744 IRX.Volume_mva200 200 Day MA
2745 IRX.Volume_mva050 50 Day MA
2749 IRX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2751 IRX.Adjusted_SmoothDer Derivative of Smoothed
2752 IRX.Adjusted_Log Log of
2753 IRX.Adjusted_mva200 200 Day MA
2754 IRX.Adjusted_mva050 50 Day MA
2758 DCOILWTICO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2760 DCOILWTICO_SmoothDer Derivative of Smoothed Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2761 DCOILWTICO_Log Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2762 DCOILWTICO_mva200 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 200 Day MA
2763 DCOILWTICO_mva050 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 50 Day MA
2767 DCOILBRENTEU_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: Brent - Europe
2769 DCOILBRENTEU_SmoothDer Derivative of Smoothed Crude Oil Prices: Brent - Europe
2771 DCOILBRENTEU_mva200 Crude Oil Prices: Brent - Europe 200 Day MA
2772 DCOILBRENTEU_mva050 Crude Oil Prices: Brent - Europe 50 Day MA
2780 NEWORDER_mva200 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
2787 ALTSALES_SmoothDer Derivative of Smoothed Light Weight Vehicle Sales: Autos and Light Trucks
2796 ICSA_SmoothDer Derivative of Smoothed Initial Jobless Claims
2839 GSPC.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2841 GSPC.Volume_SmoothDer Derivative of Smoothed
2890 FXAIX.Volume_YoY Year over Year
2891 FXAIX.Volume_YoY4 4 Year over 4 Year
2892 FXAIX.Volume_YoY5 5 Year over 5 Year
2893 FXAIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2894 FXAIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2895 FXAIX.Volume_SmoothDer Derivative of Smoothed
2896 FXAIX.Volume_Log Log of
2897 FXAIX.Volume_mva200 200 Day MA
2898 FXAIX.Volume_mva050 50 Day MA
2944 FTIHX.Volume_YoY Year over Year
2945 FTIHX.Volume_YoY4 4 Year over 4 Year
2946 FTIHX.Volume_YoY5 5 Year over 5 Year
2947 FTIHX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2948 FTIHX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2949 FTIHX.Volume_SmoothDer Derivative of Smoothed
2950 FTIHX.Volume_Log Log of
2951 FTIHX.Volume_mva200 200 Day MA
2952 FTIHX.Volume_mva050 50 Day MA
2998 MDIZX.Volume_YoY Year over Year
2999 MDIZX.Volume_YoY4 4 Year over 4 Year
3000 MDIZX.Volume_YoY5 5 Year over 5 Year
3001 MDIZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3002 MDIZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3003 MDIZX.Volume_SmoothDer Derivative of Smoothed
3004 MDIZX.Volume_Log Log of
3005 MDIZX.Volume_mva200 200 Day MA
3006 MDIZX.Volume_mva050 50 Day MA
3052 DODIX.Volume_YoY Year over Year
3053 DODIX.Volume_YoY4 4 Year over 4 Year
3054 DODIX.Volume_YoY5 5 Year over 5 Year
3055 DODIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3056 DODIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3057 DODIX.Volume_SmoothDer Derivative of Smoothed
3058 DODIX.Volume_Log Log of
3059 DODIX.Volume_mva200 200 Day MA
3060 DODIX.Volume_mva050 50 Day MA
3106 RLG.Volume_YoY Year over Year
3107 RLG.Volume_YoY4 4 Year over 4 Year
3108 RLG.Volume_YoY5 5 Year over 5 Year
3109 RLG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3110 RLG.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3111 RLG.Volume_SmoothDer Derivative of Smoothed
3112 RLG.Volume_Log Log of
3113 RLG.Volume_mva200 200 Day MA
3114 RLG.Volume_mva050 50 Day MA
3165 DJI.Volume_SmoothDer Derivative of Smoothed
3167 DJI.Volume_mva200 200 Day MA
3217 STOXX50E.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3219 STOXX50E.Volume_SmoothDer Derivative of Smoothed
3220 STOXX50E.Volume_Log Log of
3221 STOXX50E.Volume_mva200 200 Day MA
3271 EFA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3273 EFA.Volume_SmoothDer Derivative of Smoothed
3275 EFA.Volume_mva200 200 Day MA
3292 GDP_Log Log of Gross Domestic Product
3293 GDP_mva200 Gross Domestic Product 200 Day MA
3294 GDP_mva050 Gross Domestic Product 50 Day MA
3300 FNDEFX_SmoothDer Derivative of Smoothed Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3301 FNDEFX_Log Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3302 FNDEFX_mva200 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3303 FNDEFX_mva050 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3307 FDEFX_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3310 FDEFX_Log Log of Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3319 GDPNOW_Log Log of Fed Atlanta GDPNow
3328 GDPC1_Log Log of Real Gross Domestic Product
3329 GDPC1_mva200 Real Gross Domestic Product 200 Day MA
3330 GDPC1_mva050 Real Gross Domestic Product 50 Day MA
3337 GDPDEF_Log Log of Gross Domestic Product: Implicit Price Deflator
3338 GDPDEF_mva200 Gross Domestic Product: Implicit Price Deflator 200 Day MA
3339 GDPDEF_mva050 Gross Domestic Product: Implicit Price Deflator 50 Day MA
3381 VIG.Volume_SmoothDer Derivative of Smoothed
3401 WLRRAL_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 200 Day MA
3402 WLRRAL_mva050 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 50 Day MA
3403 FEDFUNDS_YoY Effective Federal Funds Rate Year over Year
3406 FEDFUNDS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Effective Federal Funds Rate
3408 FEDFUNDS_SmoothDer Derivative of Smoothed Effective Federal Funds Rate
3409 FEDFUNDS_Log Log of Effective Federal Funds Rate
3410 FEDFUNDS_mva200 Effective Federal Funds Rate 200 Day MA
3411 FEDFUNDS_mva050 Effective Federal Funds Rate 50 Day MA
3418 GPDI_Log Log of Gross Private Domestic Investment
3419 GPDI_mva200 Gross Private Domestic Investment 200 Day MA
3420 GPDI_mva050 Gross Private Domestic Investment 50 Day MA
3421 W790RC1Q027SBEA_YoY Net domestic investment: Private: Domestic busines Year over Year
3427 W790RC1Q027SBEA_Log Log of Net domestic investment: Private: Domestic busines
3428 W790RC1Q027SBEA_mva200 Net domestic investment: Private: Domestic busines 200 Day MA
3429 W790RC1Q027SBEA_mva050 Net domestic investment: Private: Domestic busines 50 Day MA
3430 MZMV_YoY Velocity of MZM Money Stock Year over Year
3436 MZMV_Log Log of Velocity of MZM Money Stock
3437 MZMV_mva200 Velocity of MZM Money Stock 200 Day MA
3438 MZMV_mva050 Velocity of MZM Money Stock 50 Day MA
3444 M1_SmoothDer Derivative of Smoothed M1 Money Stock
3445 M1_Log Log of M1 Money Stock
3446 M1_mva200 M1 Money Stock 200 Day MA
3447 M1_mva050 M1 Money Stock 50 Day MA
3453 M2_SmoothDer Derivative of Smoothed M2 Money Stock
3454 M2_Log Log of M2 Money Stock
3455 M2_mva200 M2 Money Stock 200 Day MA
3456 M2_mva050 M2 Money Stock 50 Day MA
3463 OPHNFB_Log Log of Nonfarm Business Sector: Real Output Per Hour of All Persons
3464 OPHNFB_mva200 Nonfarm Business Sector: Real Output Per Hour of All Persons 200 Day MA
3465 OPHNFB_mva050 Nonfarm Business Sector: Real Output Per Hour of All Persons 50 Day MA
3469 IPMAN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Industrial Production: Manufacturing (NAICS)
3472 IPMAN_Log Log of Industrial Production: Manufacturing (NAICS)
3473 IPMAN_mva200 Industrial Production: Manufacturing (NAICS) 200 Day MA
3474 IPMAN_mva050 Industrial Production: Manufacturing (NAICS) 50 Day MA
3482 IWD.Open_mva200 200 Day MA
3491 IWD.High_mva200 200 Day MA
3509 IWD.Close_mva200 200 Day MA
3516 IWD.Volume_SmoothDer Derivative of Smoothed
3521 IWD.Adjusted_YoY4 4 Year over 4 Year
3527 IWD.Adjusted_mva200 200 Day MA
3532 GS5_Smooth Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3534 GS5_SmoothDer Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3535 GS5_Log Log of 5-Year Treasury Constant Maturity Rate
3536 GS5_mva200 5-Year Treasury Constant Maturity Rate 200 Day MA
3537 GS5_mva050 5-Year Treasury Constant Maturity Rate 50 Day MA
3543 PSAVERT_SmoothDer Derivative of Smoothed Personal Saving Rate
3550 VIXCLS_Smooth Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3552 VIXCLS_SmoothDer Derivative of Smoothed CBOE Volatility Index
3556 VXX.Open_YoY Year over Year
3559 VXX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3561 VXX.Open_SmoothDer Derivative of Smoothed
3568 VXX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3570 VXX.High_SmoothDer Derivative of Smoothed
3574 VXX.Low_YoY Year over Year
3577 VXX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3579 VXX.Low_SmoothDer Derivative of Smoothed
3583 VXX.Close_YoY Year over Year
3586 VXX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3588 VXX.Close_SmoothDer Derivative of Smoothed
3594 VXX.Volume_YoY5 5 Year over 5 Year
3598 VXX.Volume_Log Log of
3601 VXX.Adjusted_YoY Year over Year
3604 VXX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3606 VXX.Adjusted_SmoothDer Derivative of Smoothed
3610 HOUST1F_YoY Privately Owned Housing Starts: 1-Unit Structures Year over Year
3613 HOUST1F_Smooth Savitsky-Golay Smoothed (p=3, n=365) Privately Owned Housing Starts: 1-Unit Structures
3617 HOUST1F_mva200 Privately Owned Housing Starts: 1-Unit Structures 200 Day MA
3618 HOUST1F_mva050 Privately Owned Housing Starts: 1-Unit Structures 50 Day MA
3625 GFDEBTN_Log Log of Federal Debt: Total Public Debt
3626 GFDEBTN_mva200 Federal Debt: Total Public Debt 200 Day MA
3627 GFDEBTN_mva050 Federal Debt: Total Public Debt 50 Day MA
3631 HOUST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Housing Starts: Total: New Privately Owned Housing Units Started
3633 HOUST_SmoothDer Derivative of Smoothed Housing Starts: Total: New Privately Owned Housing Units Started
3634 HOUST_Log Log of Housing Starts: Total: New Privately Owned Housing Units Started
3635 HOUST_mva200 Housing Starts: Total: New Privately Owned Housing Units Started 200 Day MA
3636 HOUST_mva050 Housing Starts: Total: New Privately Owned Housing Units Started 50 Day MA
3640 MSPUS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Median Sales Price of Houses Sold for the United States
3643 MSPUS_Log Log of Median Sales Price of Houses Sold for the United States
3662 DGORDER_mva200 Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
3667 CSUSHPINSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P/Case-Shiller U.S. National Home Price Index (NSA)
3670 CSUSHPINSA_Log Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
3671 CSUSHPINSA_mva200 S&P/Case-Shiller U.S. National Home Price Index (NSA) 200 Day MA
3672 CSUSHPINSA_mva050 S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
3673 GFDEGDQ188S_YoY Federal Debt: Total Public Debt as Percent of Gross Domestic Product Year over Year
3678 GFDEGDQ188S_SmoothDer Derivative of Smoothed Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3679 GFDEGDQ188S_Log Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3681 GFDEGDQ188S_mva050 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 50 Day MA
3682 FYFSD_YoY Federal Surplus or Deficit Year over Year
3688 FYFSD_Log Log of Federal Surplus or Deficit
3689 FYFSD_mva200 Federal Surplus or Deficit 200 Day MA
3690 FYFSD_mva050 Federal Surplus or Deficit 50 Day MA
3691 FYFSGDA188S_YoY Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
3696 FYFSGDA188S_SmoothDer Derivative of Smoothed Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3697 FYFSGDA188S_Log Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3698 FYFSGDA188S_mva200 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
3699 FYFSGDA188S_mva050 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
3703 GDX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3704 GDX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3705 GDX.Open_SmoothDer Derivative of Smoothed
3708 GDX.Open_mva050 50 Day MA
3712 GDX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3713 GDX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3714 GDX.High_SmoothDer Derivative of Smoothed
3717 GDX.High_mva050 50 Day MA
3721 GDX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3722 GDX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3723 GDX.Low_SmoothDer Derivative of Smoothed
3726 GDX.Low_mva050 50 Day MA
3730 GDX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3731 GDX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3732 GDX.Close_SmoothDer Derivative of Smoothed
3733 GDX.Close_Log Log of
3735 GDX.Close_mva050 50 Day MA
3739 GDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3741 GDX.Volume_SmoothDer Derivative of Smoothed
3748 GDX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3749 GDX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3750 GDX.Adjusted_SmoothDer Derivative of Smoothed
3751 GDX.Adjusted_Log Log of
3753 GDX.Adjusted_mva050 50 Day MA
3757 XLE.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3759 XLE.Open_SmoothDer Derivative of Smoothed
3761 XLE.Open_mva200 200 Day MA
3762 XLE.Open_mva050 50 Day MA
3766 XLE.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3768 XLE.High_SmoothDer Derivative of Smoothed
3770 XLE.High_mva200 200 Day MA
3771 XLE.High_mva050 50 Day MA
3773 XLE.Low_YoY4 4 Year over 4 Year
3775 XLE.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3776 XLE.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3777 XLE.Low_SmoothDer Derivative of Smoothed
3779 XLE.Low_mva200 200 Day MA
3780 XLE.Low_mva050 50 Day MA
3784 XLE.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3786 XLE.Close_SmoothDer Derivative of Smoothed
3788 XLE.Close_mva200 200 Day MA
3789 XLE.Close_mva050 50 Day MA
3793 XLE.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3795 XLE.Volume_SmoothDer Derivative of Smoothed
3802 XLE.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3804 XLE.Adjusted_SmoothDer Derivative of Smoothed
3806 XLE.Adjusted_mva200 200 Day MA
3807 XLE.Adjusted_mva050 50 Day MA
3811 GSG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3813 GSG.Open_SmoothDer Derivative of Smoothed
3815 GSG.Open_mva200 200 Day MA
3816 GSG.Open_mva050 50 Day MA
3820 GSG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3822 GSG.High_SmoothDer Derivative of Smoothed
3824 GSG.High_mva200 200 Day MA
3825 GSG.High_mva050 50 Day MA
3829 GSG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3831 GSG.Low_SmoothDer Derivative of Smoothed
3833 GSG.Low_mva200 200 Day MA
3834 GSG.Low_mva050 50 Day MA
3838 GSG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3840 GSG.Close_SmoothDer Derivative of Smoothed
3842 GSG.Close_mva200 200 Day MA
3843 GSG.Close_mva050 50 Day MA
3847 GSG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3849 GSG.Volume_SmoothDer Derivative of Smoothed
3851 GSG.Volume_mva200 200 Day MA
3856 GSG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3858 GSG.Adjusted_SmoothDer Derivative of Smoothed
3860 GSG.Adjusted_mva200 200 Day MA
3861 GSG.Adjusted_mva050 50 Day MA
3865 WALCL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets
3869 WALCL_mva200 All Federal Reserve Banks: Total Assets 200 Day MA
3870 WALCL_mva050 All Federal Reserve Banks: Total Assets 50 Day MA
3877 OUTMS_Log Log of Manufacturing Sector: Real Output
3878 OUTMS_mva200 Manufacturing Sector: Real Output 200 Day MA
3879 OUTMS_mva050 Manufacturing Sector: Real Output 50 Day MA
3880 MANEMP_YoY All Employees: Manufacturing Year over Year
3883 MANEMP_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Employees: Manufacturing
3886 MANEMP_Log Log of All Employees: Manufacturing
3887 MANEMP_mva200 All Employees: Manufacturing 200 Day MA
3888 MANEMP_mva050 All Employees: Manufacturing 50 Day MA
3894 PRS30006163_SmoothDer Derivative of Smoothed Manufacturing Sector: Real Output Per Person
3895 PRS30006163_Log Log of Manufacturing Sector: Real Output Per Person
3901 BAMLC0A3CA_Smooth Savitsky-Golay Smoothed (p=3, n=365) ICE BofAML US Corporate A Option-Adjusted Spread
3903 BAMLC0A3CA_SmoothDer Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
3905 BAMLC0A3CA_mva200 ICE BofAML US Corporate A Option-Adjusted Spread 200 Day MA
3906 BAMLC0A3CA_mva050 ICE BofAML US Corporate A Option-Adjusted Spread 50 Day MA
3909 AAA_YoY5 Moody’s Seasoned Aaa Corporate Bond Yield 5 Year over 5 Year
3910 AAA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Moody’s Seasoned Aaa Corporate Bond Yield
3912 AAA_SmoothDer Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
3913 AAA_Log Log of Moody’s Seasoned Aaa Corporate Bond Yield
3914 AAA_mva200 Moody’s Seasoned Aaa Corporate Bond Yield 200 Day MA
3915 AAA_mva050 Moody’s Seasoned Aaa Corporate Bond Yield 50 Day MA
3919 SOFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate
3921 SOFR_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate
3923 SOFR_mva200 Secured Overnight Financing Rate 200 Day MA
3924 SOFR_mva050 Secured Overnight Financing Rate 50 Day MA
3928 SOFRVOL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
3930 SOFRVOL_SmoothDer Derivative of Smoothed Secured Overnight Financing Volume
3932 SOFRVOL_mva200 Secured Overnight Financing Volume 200 Day MA
3934 SOFR99_YoY Secured Overnight Financing Rate: 99th Percentile Year over Year
3935 SOFR99_YoY4 Secured Overnight Financing Rate: 99th Percentile 4 Year over 4 Year
3936 SOFR99_YoY5 Secured Overnight Financing Rate: 99th Percentile 5 Year over 5 Year
3937 SOFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile
3939 SOFR99_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile
3940 SOFR99_Log Log of Secured Overnight Financing Rate: 99th Percentile
3941 SOFR99_mva200 Secured Overnight Financing Rate: 99th Percentile 200 Day MA
3942 SOFR99_mva050 Secured Overnight Financing Rate: 99th Percentile 50 Day MA
3944 SOFR75_YoY4 Secured Overnight Financing Rate: 75th Percentile 4 Year over 4 Year
3945 SOFR75_YoY5 Secured Overnight Financing Rate: 75th Percentile 5 Year over 5 Year
3946 SOFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 75th Percentile
3948 SOFR75_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 75th Percentile
3949 SOFR75_Log Log of Secured Overnight Financing Rate: 75th Percentile
3950 SOFR75_mva200 Secured Overnight Financing Rate: 75th Percentile 200 Day MA
3951 SOFR75_mva050 Secured Overnight Financing Rate: 75th Percentile 50 Day MA
3955 SOFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 25th Percentile
3957 SOFR25_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 25th Percentile
3958 SOFR25_Log Log of Secured Overnight Financing Rate: 25th Percentile
3959 SOFR25_mva200 Secured Overnight Financing Rate: 25th Percentile 200 Day MA
3960 SOFR25_mva050 Secured Overnight Financing Rate: 25th Percentile 50 Day MA
3961 SOFR1_YoY Secured Overnight Financing Rate: 1st Percentile Year over Year
3964 SOFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 1st Percentile
3966 SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 1st Percentile
3967 SOFR1_Log Log of Secured Overnight Financing Rate: 1st Percentile
3968 SOFR1_mva200 Secured Overnight Financing Rate: 1st Percentile 200 Day MA
3969 SOFR1_mva050 Secured Overnight Financing Rate: 1st Percentile 50 Day MA
3973 OBFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate
3975 OBFR_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate
3976 OBFR_Log Log of Overnight Bank Funding Rate
3977 OBFR_mva200 Overnight Bank Funding Rate 200 Day MA
3978 OBFR_mva050 Overnight Bank Funding Rate 50 Day MA
3979 OBFR99_YoY Overnight Bank Funding Rate: 99th Percentile Year over Year
3981 OBFR99_YoY5 Overnight Bank Funding Rate: 99th Percentile 5 Year over 5 Year
3982 OBFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 99th Percentile
3983 OBFR99_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Overnight Bank Funding Rate: 99th Percentile
3984 OBFR99_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 99th Percentile
3985 OBFR99_Log Log of Overnight Bank Funding Rate: 99th Percentile
3986 OBFR99_mva200 Overnight Bank Funding Rate: 99th Percentile 200 Day MA
3987 OBFR99_mva050 Overnight Bank Funding Rate: 99th Percentile 50 Day MA
3991 OBFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 75th Percentile
3993 OBFR75_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 75th Percentile
3994 OBFR75_Log Log of Overnight Bank Funding Rate: 75th Percentile
3995 OBFR75_mva200 Overnight Bank Funding Rate: 75th Percentile 200 Day MA
3996 OBFR75_mva050 Overnight Bank Funding Rate: 75th Percentile 50 Day MA
4000 OBFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 25th Percentile
4002 OBFR25_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 25th Percentile
4004 OBFR25_mva200 Overnight Bank Funding Rate: 25th Percentile 200 Day MA
4005 OBFR25_mva050 Overnight Bank Funding Rate: 25th Percentile 50 Day MA
4009 OBFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 1st Percentile
4011 OBFR1_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 1st Percentile
4013 OBFR1_mva200 Overnight Bank Funding Rate: 1st Percentile 200 Day MA
4014 OBFR1_mva050 Overnight Bank Funding Rate: 1st Percentile 50 Day MA
4020 RPONTSYD_SmoothDer Derivative of Smoothed Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4021 RPONTSYD_Log Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4024 IOER_YoY Interest Rate on Excess Reserves Year over Year
4030 IOER_Log Log of Interest Rate on Excess Reserves
4031 IOER_mva200 Interest Rate on Excess Reserves 200 Day MA
4032 IOER_mva050 Interest Rate on Excess Reserves 50 Day MA
4042 EXCSRESNW_YoY Excess Reserves of Depository Institutions Year over Year
4043 EXCSRESNW_YoY4 Excess Reserves of Depository Institutions 4 Year over 4 Year
4048 EXCSRESNW_Log Log of Excess Reserves of Depository Institutions
4049 EXCSRESNW_mva200 Excess Reserves of Depository Institutions 200 Day MA
4050 EXCSRESNW_mva050 Excess Reserves of Depository Institutions 50 Day MA
4051 ECBASSETS_YoY Central Bank Assets for Euro Area (11-19 Countries) Year over Year
4057 ECBASSETS_Log Log of Central Bank Assets for Euro Area (11-19 Countries)
4058 ECBASSETS_mva200 Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
4059 ECBASSETS_mva050 Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
4063 EUNNGDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
4066 EUNNGDP_Log Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
4067 EUNNGDP_mva200 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
4068 EUNNGDP_mva050 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
4083 CURRENCY_SmoothDer Derivative of Smoothed Currency Component of M1 (Seasonally Adjusted)
4084 CURRENCY_Log Log of Currency Component of M1 (Seasonally Adjusted)
4085 CURRENCY_mva200 Currency Component of M1 (Seasonally Adjusted) 200 Day MA
4086 CURRENCY_mva050 Currency Component of M1 (Seasonally Adjusted) 50 Day MA
4090 WCURRNS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1
4093 WCURRNS_Log Log of Currency Component of M1
4094 WCURRNS_mva200 Currency Component of M1 200 Day MA
4095 WCURRNS_mva050 Currency Component of M1 50 Day MA
4108 PRS88003193_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial Corporations Sector: Unit Profits
4110 PRS88003193_SmoothDer Derivative of Smoothed Nonfinancial Corporations Sector: Unit Profits
4111 PRS88003193_Log Log of Nonfinancial Corporations Sector: Unit Profits
4112 PRS88003193_mva200 Nonfinancial Corporations Sector: Unit Profits 200 Day MA
4113 PRS88003193_mva050 Nonfinancial Corporations Sector: Unit Profits 50 Day MA
4117 PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index for All Commodities
4119 PPIACO_SmoothDer Derivative of Smoothed Producer Price Index for All Commodities
4120 PPIACO_Log Log of Producer Price Index for All Commodities
4121 PPIACO_mva200 Producer Price Index for All Commodities 200 Day MA
4122 PPIACO_mva050 Producer Price Index for All Commodities 50 Day MA
4126 PCUOMFGOMFG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index by Industry: Total Manufacturing Industries
4128 PCUOMFGOMFG_SmoothDer Derivative of Smoothed Producer Price Index by Industry: Total Manufacturing Industries
4129 PCUOMFGOMFG_Log Log of Producer Price Index by Industry: Total Manufacturing Industries
4130 PCUOMFGOMFG_mva200 Producer Price Index by Industry: Total Manufacturing Industries 200 Day MA
4131 PCUOMFGOMFG_mva050 Producer Price Index by Industry: Total Manufacturing Industries 50 Day MA
4144 POPTHM_Log Log of Population (U.S.)
4145 POPTHM_Log Log of Population (U.S.)
4146 POPTHM_mva200 Population (U.S.) 200 Day MA
4147 POPTHM_mva200 Population (U.S.) 200 Day MA
4148 POPTHM_mva050 Population (U.S.) 50 Day MA
4149 POPTHM_mva050 Population (U.S.) 50 Day MA
4162 POPTHM.1_Log Log of
4163 POPTHM.1_Log Log of
4164 POPTHM.1_mva200 200 Day MA
4165 POPTHM.1_mva200 200 Day MA
4166 POPTHM.1_mva050 50 Day MA
4167 POPTHM.1_mva050 50 Day MA
4171 CLF16OV_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, SA
4173 CLF16OV_SmoothDer Derivative of Smoothed Civilian Labor Force Level, SA
4174 CLF16OV_Log Log of Civilian Labor Force Level, SA
4175 CLF16OV_mva200 Civilian Labor Force Level, SA 200 Day MA
4176 CLF16OV_mva050 Civilian Labor Force Level, SA 50 Day MA
4177 LNU01000000_YoY Civilian Labor Force Level, NSA Year over Year
4180 LNU01000000_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, NSA
4182 LNU01000000_SmoothDer Derivative of Smoothed Civilian Labor Force Level, NSA
4183 LNU01000000_Log Log of Civilian Labor Force Level, NSA
4184 LNU01000000_mva200 Civilian Labor Force Level, NSA 200 Day MA
4185 LNU01000000_mva050 Civilian Labor Force Level, NSA 50 Day MA
4186 LNU03000000_YoY Unemployment Level (NSA) Year over Year
4191 LNU03000000_SmoothDer Derivative of Smoothed Unemployment Level (NSA)
4200 UNEMPLOY_SmoothDer Derivative of Smoothed Unemployment Level, seasonally adjusted
4207 RSAFS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Advance Retail Sales: Retail and Food Services
4209 RSAFS_SmoothDer Derivative of Smoothed Advance Retail Sales: Retail and Food Services
4210 RSAFS_Log Log of Advance Retail Sales: Retail and Food Services
4211 RSAFS_mva200 Advance Retail Sales: Retail and Food Services 200 Day MA
4212 RSAFS_mva050 Advance Retail Sales: Retail and Food Services 50 Day MA
4218 FRGSHPUSM649NCIS_SmoothDer Derivative of Smoothed Cass Freight Index: Shipments
4223 BOPGTB_YoY4 Trade Balance: Goods, Balance of Payments Basis (SA) 4 Year over 4 Year
4228 BOPGTB_Log Log of Trade Balance: Goods, Balance of Payments Basis (SA)
4236 TERMCBPER24NS_SmoothDer Derivative of Smoothed Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4245 A065RC1A027NBEA_SmoothDer Derivative of Smoothed Personal income (NSA)
4246 A065RC1A027NBEA_Log Log of Personal income (NSA)
4247 A065RC1A027NBEA_mva200 Personal income (NSA) 200 Day MA
4248 A065RC1A027NBEA_mva050 Personal income (NSA) 50 Day MA
4252 PI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal income (SA)
4254 PI_SmoothDer Derivative of Smoothed Personal income (SA)
4255 PI_Log Log of Personal income (SA)
4256 PI_mva200 Personal income (SA) 200 Day MA
4257 PI_mva050 Personal income (SA) 50 Day MA
4261 PCE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures (SA)
4263 PCE_SmoothDer Derivative of Smoothed Personal Consumption Expenditures (SA)
4264 PCE_Log Log of Personal Consumption Expenditures (SA)
4265 PCE_mva200 Personal Consumption Expenditures (SA) 200 Day MA
4266 PCE_mva050 Personal Consumption Expenditures (SA) 50 Day MA
4270 A053RC1Q027SBEA_Smooth Savitsky-Golay Smoothed (p=3, n=365) National income: Corporate profits before tax (without IVA and CCAdj)
4272 A053RC1Q027SBEA_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj)
4273 A053RC1Q027SBEA_Log Log of National income: Corporate profits before tax (without IVA and CCAdj)
4279 CPROFIT_Smooth Savitsky-Golay Smoothed (p=3, n=365) Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4282 CPROFIT_Log Log of Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4283 CPROFIT_mva200 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 200 Day MA
4284 CPROFIT_mva050 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 50 Day MA
4324 SPY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4326 SPY.Volume_SmoothDer Derivative of Smoothed
4328 SPY.Volume_mva200 200 Day MA
4380 MDY.Volume_SmoothDer Derivative of Smoothed
4382 MDY.Volume_mva200 200 Day MA
4434 EES.Volume_SmoothDer Derivative of Smoothed
4435 EES.Volume_Log Log of
4436 EES.Volume_mva200 200 Day MA
4443 EES.Adjusted_SmoothDer Derivative of Smoothed
4452 IJR.Open_SmoothDer Derivative of Smoothed
4461 IJR.High_SmoothDer Derivative of Smoothed
4470 IJR.Low_SmoothDer Derivative of Smoothed
4479 IJR.Close_SmoothDer Derivative of Smoothed
4488 IJR.Volume_SmoothDer Derivative of Smoothed
4490 IJR.Volume_mva200 200 Day MA
4497 IJR.Adjusted_SmoothDer Derivative of Smoothed
4537 VGSTX.Volume_YoY Year over Year
4538 VGSTX.Volume_YoY4 4 Year over 4 Year
4539 VGSTX.Volume_YoY5 5 Year over 5 Year
4540 VGSTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4541 VGSTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4542 VGSTX.Volume_SmoothDer Derivative of Smoothed
4543 VGSTX.Volume_Log Log of
4544 VGSTX.Volume_mva200 200 Day MA
4545 VGSTX.Volume_mva050 50 Day MA
4591 VFINX.Volume_YoY Year over Year
4592 VFINX.Volume_YoY4 4 Year over 4 Year
4593 VFINX.Volume_YoY5 5 Year over 5 Year
4594 VFINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4595 VFINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4596 VFINX.Volume_SmoothDer Derivative of Smoothed
4597 VFINX.Volume_Log Log of
4598 VFINX.Volume_mva200 200 Day MA
4599 VFINX.Volume_mva050 50 Day MA
4616 VOE.Open_mva200 200 Day MA
4623 VOE.High_SmoothDer Derivative of Smoothed
4625 VOE.High_mva200 200 Day MA
4634 VOE.Low_mva200 200 Day MA
4641 VOE.Close_SmoothDer Derivative of Smoothed
4643 VOE.Close_mva200 200 Day MA
4648 VOE.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4650 VOE.Volume_SmoothDer Derivative of Smoothed
4652 VOE.Volume_mva200 200 Day MA
4659 VOE.Adjusted_SmoothDer Derivative of Smoothed
4661 VOE.Adjusted_mva200 200 Day MA
4704 VOT.Volume_SmoothDer Derivative of Smoothed
4706 VOT.Volume_mva200 200 Day MA
4753 TMFGX.Volume_YoY Year over Year
4754 TMFGX.Volume_YoY4 4 Year over 4 Year
4755 TMFGX.Volume_YoY5 5 Year over 5 Year
4756 TMFGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4757 TMFGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4758 TMFGX.Volume_SmoothDer Derivative of Smoothed
4759 TMFGX.Volume_Log Log of
4760 TMFGX.Volume_mva200 200 Day MA
4761 TMFGX.Volume_mva050 50 Day MA
4866 ONEQ.Volume_SmoothDer Derivative of Smoothed
4915 FSMAX.Volume_YoY Year over Year
4916 FSMAX.Volume_YoY4 4 Year over 4 Year
4917 FSMAX.Volume_YoY5 5 Year over 5 Year
4918 FSMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4919 FSMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4920 FSMAX.Volume_SmoothDer Derivative of Smoothed
4921 FSMAX.Volume_Log Log of
4922 FSMAX.Volume_mva200 200 Day MA
4923 FSMAX.Volume_mva050 50 Day MA
4969 FXNAX.Volume_YoY Year over Year
4970 FXNAX.Volume_YoY4 4 Year over 4 Year
4971 FXNAX.Volume_YoY5 5 Year over 5 Year
4972 FXNAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4973 FXNAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4974 FXNAX.Volume_SmoothDer Derivative of Smoothed
4975 FXNAX.Volume_Log Log of
4976 FXNAX.Volume_mva200 200 Day MA
4977 FXNAX.Volume_mva050 50 Day MA
5023 HAINX.Volume_YoY Year over Year
5024 HAINX.Volume_YoY4 4 Year over 4 Year
5025 HAINX.Volume_YoY5 5 Year over 5 Year
5026 HAINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5027 HAINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5028 HAINX.Volume_SmoothDer Derivative of Smoothed
5029 HAINX.Volume_Log Log of
5030 HAINX.Volume_mva200 200 Day MA
5031 HAINX.Volume_mva050 50 Day MA
5077 HNACX.Volume_YoY Year over Year
5078 HNACX.Volume_YoY4 4 Year over 4 Year
5079 HNACX.Volume_YoY5 5 Year over 5 Year
5080 HNACX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5081 HNACX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5082 HNACX.Volume_SmoothDer Derivative of Smoothed
5083 HNACX.Volume_Log Log of
5084 HNACX.Volume_mva200 200 Day MA
5085 HNACX.Volume_mva050 50 Day MA
5134 VEU.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5136 VEU.Volume_SmoothDer Derivative of Smoothed
5138 VEU.Volume_mva200 200 Day MA
5185 VEIRX.Volume_YoY Year over Year
5186 VEIRX.Volume_YoY4 4 Year over 4 Year
5187 VEIRX.Volume_YoY5 5 Year over 5 Year
5188 VEIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5189 VEIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5190 VEIRX.Volume_SmoothDer Derivative of Smoothed
5191 VEIRX.Volume_Log Log of
5192 VEIRX.Volume_mva200 200 Day MA
5193 VEIRX.Volume_mva050 50 Day MA
5197 VEIRX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5199 VEIRX.Adjusted_SmoothDer Derivative of Smoothed
5201 VEIRX.Adjusted_mva200 200 Day MA
5208 BIL.Open_SmoothDer Derivative of Smoothed
5217 BIL.High_SmoothDer Derivative of Smoothed
5226 BIL.Low_SmoothDer Derivative of Smoothed
5235 BIL.Close_SmoothDer Derivative of Smoothed
5242 BIL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5244 BIL.Volume_SmoothDer Derivative of Smoothed
5252 BIL.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5253 BIL.Adjusted_SmoothDer Derivative of Smoothed
5254 BIL.Adjusted_Log Log of
5298 IVOO.Volume_SmoothDer Derivative of Smoothed
5299 IVOO.Volume_Log Log of
5352 VO.Volume_SmoothDer Derivative of Smoothed
5353 VO.Volume_Log Log of
5384 CZA.Low_YoY4 4 Year over 4 Year
5393 CZA.Close_YoY4 4 Year over 4 Year
5404 CZA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5406 CZA.Volume_SmoothDer Derivative of Smoothed
5407 CZA.Volume_Log Log of
5411 CZA.Adjusted_YoY4 4 Year over 4 Year
5422 VYM.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5424 VYM.Open_SmoothDer Derivative of Smoothed
5426 VYM.Open_mva200 200 Day MA
5431 VYM.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5433 VYM.High_SmoothDer Derivative of Smoothed
5435 VYM.High_mva200 200 Day MA
5440 VYM.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5442 VYM.Low_SmoothDer Derivative of Smoothed
5444 VYM.Low_mva200 200 Day MA
5447 VYM.Close_YoY4 4 Year over 4 Year
5449 VYM.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5451 VYM.Close_SmoothDer Derivative of Smoothed
5453 VYM.Close_mva200 200 Day MA
5460 VYM.Volume_SmoothDer Derivative of Smoothed
5462 VYM.Volume_mva200 200 Day MA
5467 VYM.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5469 VYM.Adjusted_SmoothDer Derivative of Smoothed
5471 VYM.Adjusted_mva200 200 Day MA
5516 ACWI.Volume_mva200 200 Day MA
5532 SLY.Open_SmoothDer Derivative of Smoothed
5541 SLY.High_SmoothDer Derivative of Smoothed
5550 SLY.Low_SmoothDer Derivative of Smoothed
5559 SLY.Close_SmoothDer Derivative of Smoothed
5568 SLY.Volume_SmoothDer Derivative of Smoothed
5569 SLY.Volume_Log Log of
5570 SLY.Volume_mva200 200 Day MA
5577 SLY.Adjusted_SmoothDer Derivative of Smoothed
5620 QQQ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5622 QQQ.Volume_SmoothDer Derivative of Smoothed
5624 QQQ.Volume_mva200 200 Day MA
5674 HYMB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5676 HYMB.Volume_SmoothDer Derivative of Smoothed
5677 HYMB.Volume_Log Log of
5678 HYMB.Volume_mva200 200 Day MA
5692 GOLD.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5693 GOLD.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5694 GOLD.Open_SmoothDer Derivative of Smoothed
5695 GOLD.Open_Log Log of
5697 GOLD.Open_mva050 50 Day MA
5701 GOLD.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5702 GOLD.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5703 GOLD.High_SmoothDer Derivative of Smoothed
5706 GOLD.High_mva050 50 Day MA
5710 GOLD.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5711 GOLD.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5712 GOLD.Low_SmoothDer Derivative of Smoothed
5715 GOLD.Low_mva050 50 Day MA
5719 GOLD.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5720 GOLD.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5721 GOLD.Close_SmoothDer Derivative of Smoothed
5724 GOLD.Close_mva050 50 Day MA
5728 GOLD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5730 GOLD.Volume_SmoothDer Derivative of Smoothed
5731 GOLD.Volume_Log Log of
5733 GOLD.Volume_mva050 50 Day MA
5737 GOLD.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5738 GOLD.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5739 GOLD.Adjusted_SmoothDer Derivative of Smoothed
5742 GOLD.Adjusted_mva050 50 Day MA
5746 BKR.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5748 BKR.Open_SmoothDer Derivative of Smoothed
5749 BKR.Open_Log Log of
5750 BKR.Open_mva200 200 Day MA
5751 BKR.Open_mva050 50 Day MA
5755 BKR.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5757 BKR.High_SmoothDer Derivative of Smoothed
5759 BKR.High_mva200 200 Day MA
5760 BKR.High_mva050 50 Day MA
5764 BKR.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5766 BKR.Low_SmoothDer Derivative of Smoothed
5768 BKR.Low_mva200 200 Day MA
5769 BKR.Low_mva050 50 Day MA
5773 BKR.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5775 BKR.Close_SmoothDer Derivative of Smoothed
5777 BKR.Close_mva200 200 Day MA
5778 BKR.Close_mva050 50 Day MA
5782 BKR.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5784 BKR.Volume_SmoothDer Derivative of Smoothed
5785 BKR.Volume_Log Log of
5786 BKR.Volume_mva200 200 Day MA
5787 BKR.Volume_mva050 50 Day MA
5791 BKR.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5793 BKR.Adjusted_SmoothDer Derivative of Smoothed
5795 BKR.Adjusted_mva200 200 Day MA
5796 BKR.Adjusted_mva050 50 Day MA
5800 SLB.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5802 SLB.Open_SmoothDer Derivative of Smoothed
5804 SLB.Open_mva200 200 Day MA
5805 SLB.Open_mva050 50 Day MA
5809 SLB.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5811 SLB.High_SmoothDer Derivative of Smoothed
5813 SLB.High_mva200 200 Day MA
5814 SLB.High_mva050 50 Day MA
5818 SLB.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5820 SLB.Low_SmoothDer Derivative of Smoothed
5822 SLB.Low_mva200 200 Day MA
5823 SLB.Low_mva050 50 Day MA
5827 SLB.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5829 SLB.Close_SmoothDer Derivative of Smoothed
5831 SLB.Close_mva200 200 Day MA
5832 SLB.Close_mva050 50 Day MA
5836 SLB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5838 SLB.Volume_SmoothDer Derivative of Smoothed
5840 SLB.Volume_mva200 200 Day MA
5845 SLB.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5847 SLB.Adjusted_SmoothDer Derivative of Smoothed
5849 SLB.Adjusted_mva200 200 Day MA
5850 SLB.Adjusted_mva050 50 Day MA
5854 HAL.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5855 HAL.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5856 HAL.Open_SmoothDer Derivative of Smoothed
5857 HAL.Open_Log Log of
5858 HAL.Open_mva200 200 Day MA
5859 HAL.Open_mva050 50 Day MA
5861 HAL.High_YoY4 4 Year over 4 Year
5863 HAL.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5864 HAL.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5865 HAL.High_SmoothDer Derivative of Smoothed
5867 HAL.High_mva200 200 Day MA
5868 HAL.High_mva050 50 Day MA
5870 HAL.Low_YoY4 4 Year over 4 Year
5872 HAL.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5873 HAL.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5874 HAL.Low_SmoothDer Derivative of Smoothed
5875 HAL.Low_Log Log of
5876 HAL.Low_mva200 200 Day MA
5877 HAL.Low_mva050 50 Day MA
5879 HAL.Close_YoY4 4 Year over 4 Year
5881 HAL.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5882 HAL.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5883 HAL.Close_SmoothDer Derivative of Smoothed
5885 HAL.Close_mva200 200 Day MA
5886 HAL.Close_mva050 50 Day MA
5890 HAL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5892 HAL.Volume_SmoothDer Derivative of Smoothed
5893 HAL.Volume_Log Log of
5894 HAL.Volume_mva200 200 Day MA
5897 HAL.Adjusted_YoY4 4 Year over 4 Year
5899 HAL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5900 HAL.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5901 HAL.Adjusted_SmoothDer Derivative of Smoothed
5903 HAL.Adjusted_mva200 200 Day MA
5904 HAL.Adjusted_mva050 50 Day MA
5911 IP.Open_Log Log of
5946 IP.Volume_SmoothDer Derivative of Smoothed
5948 IP.Volume_mva200 200 Day MA
5960 PKG.Open_YoY4 4 Year over 4 Year
5962 PKG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5963 PKG.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5964 PKG.Open_SmoothDer Derivative of Smoothed
5967 PKG.Open_mva050 50 Day MA
5971 PKG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5972 PKG.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5973 PKG.High_SmoothDer Derivative of Smoothed
5976 PKG.High_mva050 50 Day MA
5980 PKG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5981 PKG.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5982 PKG.Low_SmoothDer Derivative of Smoothed
5985 PKG.Low_mva050 50 Day MA
5987 PKG.Close_YoY4 4 Year over 4 Year
5989 PKG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5991 PKG.Close_SmoothDer Derivative of Smoothed
5994 PKG.Close_mva050 50 Day MA
6005 PKG.Adjusted_YoY4 4 Year over 4 Year
6007 PKG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6009 PKG.Adjusted_SmoothDer Derivative of Smoothed
6012 PKG.Adjusted_mva050 50 Day MA
6016 UPS.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6020 UPS.Open_mva200 200 Day MA
6025 UPS.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6029 UPS.High_mva200 200 Day MA
6034 UPS.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6038 UPS.Low_mva200 200 Day MA
6043 UPS.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6047 UPS.Close_mva200 200 Day MA
6052 UPS.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6054 UPS.Volume_SmoothDer Derivative of Smoothed
6061 UPS.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6065 UPS.Adjusted_mva200 200 Day MA
6081 FDX.High_SmoothDer Derivative of Smoothed
6099 FDX.Close_SmoothDer Derivative of Smoothed
6106 FDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6110 FDX.Volume_mva200 200 Day MA
6117 FDX.Adjusted_SmoothDer Derivative of Smoothed
6126 T.Open_SmoothDer Derivative of Smoothed
6127 T.Open_Log Log of
6135 T.High_SmoothDer Derivative of Smoothed
6144 T.Low_SmoothDer Derivative of Smoothed
6153 T.Close_SmoothDer Derivative of Smoothed
6164 T.Volume_mva200 200 Day MA
6171 T.Adjusted_SmoothDer Derivative of Smoothed
6180 VZ.Open_SmoothDer Derivative of Smoothed
6189 VZ.High_SmoothDer Derivative of Smoothed
6198 VZ.Low_SmoothDer Derivative of Smoothed
6207 VZ.Close_SmoothDer Derivative of Smoothed
6214 VZ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6216 VZ.Volume_SmoothDer Derivative of Smoothed
6218 VZ.Volume_mva200 200 Day MA
6219 VZ.Volume_mva050 50 Day MA
6223 VZ.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6225 VZ.Adjusted_SmoothDer Derivative of Smoothed
6238 MULTPLSP500PERATIOMONTH_YoY S&P 500 TTM P/E Year over Year
6253 MULTPLSP500SALESQUARTER_Log Log of S&P 500 TTM Sales (Not Inflation Adjusted)
6254 MULTPLSP500SALESQUARTER_mva200 S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
6255 MULTPLSP500SALESQUARTER_mva050 S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
6259 MULTPLSP500DIVYIELDMONTH_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 Dividend Yield by Month
6261 MULTPLSP500DIVYIELDMONTH_SmoothDer Derivative of Smoothed S&P 500 Dividend Yield by Month
6265 MULTPLSP500DIVMONTH_YoY S&P 500 Dividend by Month (Inflation Adjusted) Year over Year
6271 MULTPLSP500DIVMONTH_Log Log of S&P 500 Dividend by Month (Inflation Adjusted)
6272 MULTPLSP500DIVMONTH_mva200 S&P 500 Dividend by Month (Inflation Adjusted) 200 Day MA
6273 MULTPLSP500DIVMONTH_mva050 S&P 500 Dividend by Month (Inflation Adjusted) 50 Day MA
6277 CHRISCMEHG1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6279 CHRISCMEHG1_SmoothDer Derivative of Smoothed Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6280 CHRISCMEHG1_Log Log of Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6282 CHRISCMEHG1_mva050 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 50 Day MA
6283 WWDIWLDISAIRGOODMTK1_YoY Air transport, freight Year over Year
6289 WWDIWLDISAIRGOODMTK1_Log Log of Air transport, freight
6290 WWDIWLDISAIRGOODMTK1_mva200 Air transport, freight 200 Day MA
6291 WWDIWLDISAIRGOODMTK1_mva050 Air transport, freight 50 Day MA
6295 LBMAGOLD.USD_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6297 LBMAGOLD.USD_AM_SmoothDer Derivative of Smoothed
6299 LBMAGOLD.USD_AM_mva200 200 Day MA
6300 LBMAGOLD.USD_AM_mva050 50 Day MA
6304 LBMAGOLD.USD_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6306 LBMAGOLD.USD_PM_SmoothDer Derivative of Smoothed
6308 LBMAGOLD.USD_PM_mva200 200 Day MA
6309 LBMAGOLD.USD_PM_mva050 50 Day MA
6313 LBMAGOLD.GBP_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6315 LBMAGOLD.GBP_AM_SmoothDer Derivative of Smoothed
6317 LBMAGOLD.GBP_AM_mva200 200 Day MA
6318 LBMAGOLD.GBP_AM_mva050 50 Day MA
6322 LBMAGOLD.GBP_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6324 LBMAGOLD.GBP_PM_SmoothDer Derivative of Smoothed
6326 LBMAGOLD.GBP_PM_mva200 200 Day MA
6327 LBMAGOLD.GBP_PM_mva050 50 Day MA
6331 LBMAGOLD.EURO_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6333 LBMAGOLD.EURO_AM_SmoothDer Derivative of Smoothed
6335 LBMAGOLD.EURO_AM_mva200 200 Day MA
6336 LBMAGOLD.EURO_AM_mva050 50 Day MA
6340 LBMAGOLD.EURO_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6342 LBMAGOLD.EURO_PM_SmoothDer Derivative of Smoothed
6344 LBMAGOLD.EURO_PM_mva200 200 Day MA
6345 LBMAGOLD.EURO_PM_mva050 50 Day MA
6351 PETA103600001M_SmoothDer Derivative of Smoothed U.S. Total Gasoline Retail Sales by Refiners, Monthly
6352 PETA103600001M_Log Log of U.S. Total Gasoline Retail Sales by Refiners, Monthly
6354 PETA103600001M_mva050 U.S. Total Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6360 PETA123600001M_SmoothDer Derivative of Smoothed U.S. Regular Gasoline Retail Sales by Refiners, Monthly
6361 PETA123600001M_Log Log of U.S. Regular Gasoline Retail Sales by Refiners, Monthly
6363 PETA123600001M_mva050 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6364 PETA143B00001M_YoY U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly Year over Year
6365 PETA143B00001M_YoY4 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
6366 PETA143B00001M_YoY5 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
6370 PETA143B00001M_Log Log of U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
6371 PETA143B00001M_mva200 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6372 PETA143B00001M_mva050 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6378 PETA133B00001M_SmoothDer Derivative of Smoothed U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
6379 PETA133B00001M_Log Log of U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
6380 PETA133B00001M_mva200 U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 200 Day MA
6381 PETA133B00001M_mva050 U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 50 Day MA
6385 TOTALOGNRPUSM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
6387 TOTALOGNRPUSM_SmoothDer Derivative of Smoothed Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
6388 TOTALOGNRPUSM_Log Log of Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
6389 TOTALOGNRPUSM_mva200 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 200 Day MA
6390 TOTALOGNRPUSM_mva050 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 50 Day MA
6394 TOTALPANRPUSM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Rotary Rigs in Operation, Monthly
6397 TOTALPANRPUSM_Log Log of Crude Oil Rotary Rigs in Operation, Monthly
6398 TOTALPANRPUSM_mva200 Crude Oil Rotary Rigs in Operation, Monthly 200 Day MA
6399 TOTALPANRPUSM_mva050 Crude Oil Rotary Rigs in Operation, Monthly 50 Day MA
6403 TOTALNGNRPUSM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Natural Gas Rotary Rigs in Operation, Monthly
6405 TOTALNGNRPUSM_SmoothDer Derivative of Smoothed Natural Gas Rotary Rigs in Operation, Monthly
6406 TOTALNGNRPUSM_Log Log of Natural Gas Rotary Rigs in Operation, Monthly
6407 TOTALNGNRPUSM_mva200 Natural Gas Rotary Rigs in Operation, Monthly 200 Day MA
6408 TOTALNGNRPUSM_mva050 Natural Gas Rotary Rigs in Operation, Monthly 50 Day MA
6412 BKRTotal_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Rig Count
6414 BKRTotal_SmoothDer Derivative of Smoothed Total Rig Count
6415 BKRTotal_Log Log of Total Rig Count
6416 BKRTotal_mva200 Total Rig Count 200 Day MA
6417 BKRTotal_mva050 Total Rig Count 50 Day MA
6418 BKRGas_YoY Gas Rig Count Year over Year
6421 BKRGas_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gas Rig Count
6423 BKRGas_SmoothDer Derivative of Smoothed Gas Rig Count
6424 BKRGas_Log Log of Gas Rig Count
6425 BKRGas_mva200 Gas Rig Count 200 Day MA
6426 BKRGas_mva050 Gas Rig Count 50 Day MA
6430 BKROil_Smooth Savitsky-Golay Smoothed (p=3, n=365) Oil Rig Count
6432 BKROil_SmoothDer Derivative of Smoothed Oil Rig Count
6433 BKROil_Log Log of Oil Rig Count
6434 BKROil_mva200 Oil Rig Count 200 Day MA
6435 BKROil_mva050 Oil Rig Count 50 Day MA
6436 FARMINCOME_YoY Net Farm Income Year over Year
6442 FARMINCOME_Log Log of Net Farm Income
6443 FARMINCOME_mva200 Net Farm Income 200 Day MA
6444 FARMINCOME_mva050 Net Farm Income 50 Day MA
6450 OPEARNINGSPERSHARE_SmoothDer Derivative of Smoothed Operating Earnings per Share
6451 OPEARNINGSPERSHARE_Log Log of Operating Earnings per Share
6452 OPEARNINGSPERSHARE_mva200 Operating Earnings per Share 200 Day MA
6453 OPEARNINGSPERSHARE_mva050 Operating Earnings per Share 50 Day MA
6459 AREARNINGSPERSHARE_SmoothDer Derivative of Smoothed As-Reported Earnings per Share
6460 AREARNINGSPERSHARE_Log Log of As-Reported Earnings per Share
6461 AREARNINGSPERSHARE_mva200 As-Reported Earnings per Share 200 Day MA
6462 AREARNINGSPERSHARE_mva050 As-Reported Earnings per Share 50 Day MA
6468 CASHDIVIDENDSPERSHR_SmoothDer Derivative of Smoothed Cash Dividends per Share
6469 CASHDIVIDENDSPERSHR_Log Log of Cash Dividends per Share
6470 CASHDIVIDENDSPERSHR_mva200 Cash Dividends per Share 200 Day MA
6471 CASHDIVIDENDSPERSHR_mva050 Cash Dividends per Share 50 Day MA
6477 SALESPERSHR_SmoothDer Derivative of Smoothed Sales per Share
6478 SALESPERSHR_Log Log of Sales per Share
6480 SALESPERSHR_mva050 Sales per Share 50 Day MA
6486 BOOKVALPERSHR_SmoothDer Derivative of Smoothed Book value per Share
6487 BOOKVALPERSHR_Log Log of Book value per Share
6488 BOOKVALPERSHR_mva200 Book value per Share 200 Day MA
6489 BOOKVALPERSHR_mva050 Book value per Share 50 Day MA
6490 CAPEXPERSHR_YoY Cap ex per Share Year over Year
6496 CAPEXPERSHR_Log Log of Cap ex per Share
6498 CAPEXPERSHR_mva050 Cap ex per Share 50 Day MA
6504 PRICE_SmoothDer Derivative of Smoothed Price
6505 PRICE_Log Log of Price
6506 PRICE_mva200 Price 200 Day MA
6507 PRICE_mva050 Price 50 Day MA
6513 OPEARNINGSTTM_SmoothDer Derivative of Smoothed TTM Operating Earnings
6514 OPEARNINGSTTM_Log Log of TTM Operating Earnings
6515 OPEARNINGSTTM_mva200 TTM Operating Earnings 200 Day MA
6516 OPEARNINGSTTM_mva050 TTM Operating Earnings 50 Day MA
6522 AREARNINGSTTM_SmoothDer Derivative of Smoothed TTM Reported Earnings
6523 AREARNINGSTTM_Log Log of TTM Reported Earnings
6524 AREARNINGSTTM_mva200 TTM Reported Earnings 200 Day MA
6525 AREARNINGSTTM_mva050 TTM Reported Earnings 50 Day MA
6532 FINRAMarginDebt_Log Log of Margin Debt
6536 FINRAFreeCreditMargin_YoY4 Free Credit Balances in Customers’ Securities Margin Accounts 4 Year over 4 Year
6538 FINRAFreeCreditMargin_Smooth Savitsky-Golay Smoothed (p=3, n=365) Free Credit Balances in Customers’ Securities Margin Accounts
6540 FINRAFreeCreditMargin_SmoothDer Derivative of Smoothed Free Credit Balances in Customers’ Securities Margin Accounts
6541 FINRAFreeCreditMargin_Log Log of Free Credit Balances in Customers’ Securities Margin Accounts
6543 FINRAFreeCreditMargin_mva050 Free Credit Balances in Customers’ Securities Margin Accounts 50 Day MA
6544 OCCEquityVolume_YoY Equity Options Volume Year over Year
6550 OCCEquityVolume_Log Log of Equity Options Volume
6551 OCCEquityVolume_mva200 Equity Options Volume 200 Day MA
6552 OCCEquityVolume_mva050 Equity Options Volume 50 Day MA
6553 OCCNonEquityVolume_YoY Non-Equity Options Volume Year over Year
6559 OCCNonEquityVolume_Log Log of Non-Equity Options Volume
6560 OCCNonEquityVolume_mva200 Non-Equity Options Volume 200 Day MA
6561 OCCNonEquityVolume_mva050 Non-Equity Options Volume 50 Day MA
6565 RSALESAGG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Retail and Food Services Sales (RRSFS and RSALES)
6567 RSALESAGG_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales (RRSFS and RSALES)
6569 RSALESAGG_mva200 Real Retail and Food Services Sales (RRSFS and RSALES) 200 Day MA
6577 BUSLOANS.minus.BUSLOANSNSA_Log Log of Business Loans (Montlhy) SA - NSA
6586 BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log Log of Business Loans (Montlhy) SA - NSA divided by GDP
6589 BUSLOANS.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6591 BUSLOANS.by.GDP_YoY5 Business Loans Normalized by GDP 5 Year over 5 Year
6592 BUSLOANS.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6594 BUSLOANS.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
6595 BUSLOANS.by.GDP_Log Log of Business Loans Normalized by GDP
6597 BUSLOANS.by.GDP_mva050 Business Loans Normalized by GDP 50 Day MA
6601 BUSLOANS.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burdens
6603 BUSLOANS.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burdens
6605 BUSLOANS.INTEREST_mva200 Business Loans (Monthly, SA) Adjusted Interest Burdens 200 Day MA
6606 BUSLOANS.INTEREST_mva050 Business Loans (Monthly, SA) Adjusted Interest Burdens 50 Day MA
6610 BUSLOANS.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6612 BUSLOANS.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6614 BUSLOANS.INTEREST.by.GDP_mva200 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 200 Day MA
6615 BUSLOANS.INTEREST.by.GDP_mva050 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 50 Day MA
6616 BUSLOANSNSA.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6619 BUSLOANSNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6621 BUSLOANSNSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
6622 BUSLOANSNSA.by.GDP_Log Log of Business Loans Normalized by GDP
6624 BUSLOANSNSA.by.GDP_mva050 Business Loans Normalized by GDP 50 Day MA
6625 TOTCI.by.GDP_YoY Business Loans (Weekly, SA) Normalized by GDP Year over Year
6628 TOTCI.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, SA) Normalized by GDP
6630 TOTCI.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, SA) Normalized by GDP
6633 TOTCI.by.GDP_mva050 Business Loans (Weekly, SA) Normalized by GDP 50 Day MA
6634 TOTCINSA.by.GDP_YoY Business Loans (Weekly, NSA) Normalized by GDP Year over Year
6637 TOTCINSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Normalized by GDP
6639 TOTCINSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Normalized by GDP
6640 TOTCINSA.by.GDP_Log Log of Business Loans (Weekly, NSA) Normalized by GDP
6642 TOTCINSA.by.GDP_mva050 Business Loans (Weekly, NSA) Normalized by GDP 50 Day MA
6646 TOTCINSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Adjusted Interest Burdens
6648 TOTCINSA.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Adjusted Interest Burdens
6650 TOTCINSA.INTEREST_mva200 Business Loans (Weekly, NSA) Adjusted Interest Burdens 200 Day MA
6651 TOTCINSA.INTEREST_mva050 Business Loans (Weekly, NSA) Adjusted Interest Burdens 50 Day MA
6655 TOTCINSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6657 TOTCINSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6659 TOTCINSA.INTEREST.by.GDP_mva200 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 200 Day MA
6660 TOTCINSA.INTEREST.by.GDP_mva050 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 50 Day MA
6661 W875RX1.by.GDP_YoY Real Personal Income Normalized by GDP Year over Year
6662 W875RX1.by.GDP_YoY4 Real Personal Income Normalized by GDP 4 Year over 4 Year
6666 W875RX1.by.GDP_SmoothDer Derivative of Smoothed Real Personal Income Normalized by GDP
6670 A065RC1A027NBEA.by.GDP_YoY Personal Income (NSA) Normalized by GDP Year over Year
6675 A065RC1A027NBEA.by.GDP_SmoothDer Derivative of Smoothed Personal Income (NSA) Normalized by GDP
6676 A065RC1A027NBEA.by.GDP_Log Log of Personal Income (NSA) Normalized by GDP
6682 PI.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Income (SA) Normalized by GDP
6684 PI.by.GDP_SmoothDer Derivative of Smoothed Personal Income (SA) Normalized by GDP
6685 PI.by.GDP_Log Log of Personal Income (SA) Normalized by GDP
6687 PI.by.GDP_mva050 Personal Income (SA) Normalized by GDP 50 Day MA
6693 A053RC1Q027SBEA.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
6694 A053RC1Q027SBEA.by.GDP_Log Log of National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
6700 CPROFIT.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
6702 CPROFIT.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
6703 CPROFIT.by.GDP_Log Log of National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
6706 CONSUMERNSA.by.GDP_YoY Consumer Loans Not Seasonally Adjusted divided by GDP Year over Year
6709 CONSUMERNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans Not Seasonally Adjusted divided by GDP
6713 CONSUMERNSA.by.GDP_mva200 Consumer Loans Not Seasonally Adjusted divided by GDP 200 Day MA
6715 RREACBM027NBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, NSA) divided by GDP Year over Year
6716 RREACBM027NBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, NSA) divided by GDP 4 Year over 4 Year
6718 RREACBM027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
6724 RREACBM027SBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, SA) divided by GDP Year over Year
6725 RREACBM027SBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
6726 RREACBM027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
6727 RREACBM027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
6729 RREACBM027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
6730 RREACBM027SBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, SA) divided by GDP
6732 RREACBM027SBOG.by.GDP_mva050 Residental Real Estate Loans (Monthly, SA) divided by GDP 50 Day MA
6734 RREACBW027SBOG.by.GDP_YoY4 Residental Real Estate Loans (Weekly, SA) divided by GDP 4 Year over 4 Year
6735 RREACBW027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Weekly, SA) divided by GDP 5 Year over 5 Year
6736 RREACBW027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
6738 RREACBW027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
6739 RREACBW027SBOG.by.GDP_Log Log of Residental Real Estate Loans (Weekly, SA) divided by GDP
6741 RREACBW027SBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, SA) divided by GDP 50 Day MA
6745 RREACBW027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
6747 RREACBW027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
6750 RREACBW027NBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, NSA) divided by GDP 50 Day MA
6756 UMDMNO.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6765 DGORDER.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6767 DGORDER.by.GDP_mva200 Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
6769 ASHMA.by.GDP_YoY Home Mortgages (Quarterly, NSA) divided by GDP Year over Year
6771 ASHMA.by.GDP_YoY5 Home Mortgages (Quarterly, NSA) divided by GDP 5 Year over 5 Year
6774 ASHMA.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
6775 ASHMA.by.GDP_Log Log of Home Mortgages (Quarterly, NSA) divided by GDP
6779 ASHMA.INTEREST_YoY4 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6780 ASHMA.INTEREST_YoY5 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6781 ASHMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6782 ASHMA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6783 ASHMA.INTEREST_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6784 ASHMA.INTEREST_Log Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6785 ASHMA.INTEREST_mva200 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6786 ASHMA.INTEREST_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6788 ASHMA.INTEREST.by.GDP_YoY4 4 Year over 4 Year
6789 ASHMA.INTEREST.by.GDP_YoY5 5 Year over 5 Year
6790 ASHMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6791 ASHMA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6792 ASHMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed
6793 ASHMA.INTEREST.by.GDP_Log Log of
6794 ASHMA.INTEREST.by.GDP_mva200 200 Day MA
6795 ASHMA.INTEREST.by.GDP_mva050 50 Day MA
6799 CONSUMERNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6803 CONSUMERNSA.INTEREST_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
6805 CONSUMERNSA.INTEREST.by.GDP_YoY Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP Year over Year
6808 CONSUMERNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6814 TOTLNNSA_YoY Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) Year over Year
6820 TOTLNNSA_Log Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6821 TOTLNNSA_mva200 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
6822 TOTLNNSA_mva050 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
6823 TOTLNNSA.by.GDP_YoY Total Loans Not Seasonally Adjusted divided by GDP Year over Year
6826 TOTLNNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted divided by GDP
6828 TOTLNNSA.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted divided by GDP
6829 TOTLNNSA.by.GDP_Log Log of Total Loans Not Seasonally Adjusted divided by GDP
6831 TOTLNNSA.by.GDP_mva050 Total Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6835 TOTLNNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
6837 TOTLNNSA.INTEREST_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burdens
6839 TOTLNNSA.INTEREST_mva200 Total Loans Not Seasonally Adjusted Interest Burdens 200 Day MA
6840 TOTLNNSA.INTEREST_mva050 Total Loans Not Seasonally Adjusted Interest Burdens 50 Day MA
6844 TOTLNNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6846 TOTLNNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6848 TOTLNNSA.INTEREST.by.GDP_mva200 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 200 Day MA
6849 TOTLNNSA.INTEREST.by.GDP_mva050 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 50 Day MA
6859 EXCSRESNW.by.GDP_YoY Excess Reserves of Depository Institutions Divided by GDP Year over Year
6860 EXCSRESNW.by.GDP_YoY4 Excess Reserves of Depository Institutions Divided by GDP 4 Year over 4 Year
6864 EXCSRESNW.by.GDP_SmoothDer Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
6865 EXCSRESNW.by.GDP_Log Log of Excess Reserves of Depository Institutions Divided by GDP
6875 WLRRAL.by.GDP_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 200 Day MA
6876 WLRRAL.by.GDP_mva050 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 50 Day MA
6880 SOFR99.minus.SOFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6882 SOFR99.minus.SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6884 SOFR99.minus.SOFR1_mva200 Secured Overnight Financing Rate: 99th Percentile - 1st Percentile 200 Day MA
6885 SOFR99.minus.SOFR1_mva050 Secured Overnight Financing Rate: 99th Percentile - 1st Percentile 50 Day MA
6891 EXPCH.minus.IMPCH_SmoothDer Derivative of Smoothed U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6892 EXPCH.minus.IMPCH_Log Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6898 EXPMX.minus.IMPMX_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6900 EXPMX.minus.IMPMX_SmoothDer Derivative of Smoothed
6901 EXPMX.minus.IMPMX_Log Log of
6905 SRPSABSNNCB.by.GDP_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 4 Year over 4 Year
6906 SRPSABSNNCB.by.GDP_YoY5 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 5 Year over 5 Year
6909 SRPSABSNNCB.by.GDP_SmoothDer Derivative of Smoothed Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6910 SRPSABSNNCB.by.GDP_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6911 SRPSABSNNCB.by.GDP_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 200 Day MA
6912 SRPSABSNNCB.by.GDP_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 50 Day MA
6913 ASTLL.by.GDP_YoY All sectors; total loans; liability, Level (NSA) Divided by GDP Year over Year
6918 ASTLL.by.GDP_SmoothDer Derivative of Smoothed All sectors; total loans; liability, Level (NSA) Divided by GDP
6919 ASTLL.by.GDP_Log Log of All sectors; total loans; liability, Level (NSA) Divided by GDP
6922 ASFMA.by.GDP_YoY All sectors; farm mortgages; asset, Level (NSA) Divided by GDP Year over Year
6927 ASFMA.by.GDP_SmoothDer Derivative of Smoothed All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
6928 ASFMA.by.GDP_Log Log of All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
6931 ASFMA.by.ASTLL_YoY All sectors; total loans Divided by farm mortgages Year over Year
6936 ASFMA.by.ASTLL_SmoothDer Derivative of Smoothed All sectors; total loans Divided by farm mortgages
6937 ASFMA.by.ASTLL_Log Log of All sectors; total loans Divided by farm mortgages
6941 ASFMA.INTEREST_YoY4 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6942 ASFMA.INTEREST_YoY5 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6943 ASFMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6944 ASFMA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6945 ASFMA.INTEREST_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6946 ASFMA.INTEREST_Log Log of Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6947 ASFMA.INTEREST_mva200 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6948 ASFMA.INTEREST_mva050 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6950 ASFMA.INTEREST.by.GDP_YoY4 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 4 Year over 4 Year
6951 ASFMA.INTEREST.by.GDP_YoY5 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 5 Year over 5 Year
6952 ASFMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6953 ASFMA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6954 ASFMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6955 ASFMA.INTEREST.by.GDP_Log Log of Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6956 ASFMA.INTEREST.by.GDP_mva200 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 200 Day MA
6957 ASFMA.INTEREST.by.GDP_mva050 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 50 Day MA
6958 FARMINCOME.by.GDP_YoY Farm Income (Annual, NSA) Divided by GDP Year over Year
6963 FARMINCOME.by.GDP_SmoothDer Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
6964 FARMINCOME.by.GDP_Log Log of Farm Income (Annual, NSA) Divided by GDP
6977 WALCL.by.GDP_YoY4 All Federal Reserve Banks: Total Assets Divided by GDP 4 Year over 4 Year
6979 WALCL.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets Divided by GDP
6981 WALCL.by.GDP_SmoothDer Derivative of Smoothed All Federal Reserve Banks: Total Assets Divided by GDP
6983 WALCL.by.GDP_mva200 All Federal Reserve Banks: Total Assets Divided by GDP 200 Day MA
6984 WALCL.by.GDP_mva050 All Federal Reserve Banks: Total Assets Divided by GDP 50 Day MA
6985 ECBASSETS.by.EUNNGDP_YoY Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
6990 ECBASSETS.by.EUNNGDP_SmoothDer Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6991 ECBASSETS.by.EUNNGDP_Log Log of Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6999 DGS30TO10_SmoothDer Derivative of Smoothed Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7000 DGS30TO10_Log Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7009 DGS10TO1_Log Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7018 DGS10TO2_Log Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7024 DGS10TOTB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7026 DGS10TOTB3MS_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7027 DGS10TOTB3MS_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7028 DGS10TOTB3MS_mva200 Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 200 Day MA
7029 DGS10TOTB3MS_mva050 Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 50 Day MA
7033 DGS10TODTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7035 DGS10TODTB3_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7036 DGS10TODTB3_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7037 DGS10TODTB3_mva200 Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 200 Day MA
7038 DGS10TODTB3_mva050 Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 50 Day MA
7048 LNU03000000BYPOPTHM_YoY Unemployment level (NSA) / Population Year over Year
7053 LNU03000000BYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level (NSA) / Population
7062 UNEMPLOYBYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level, seasonally adjusted / Population
7069 NPPTTLBYPOPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) ADP Private Employment / Population
7071 NPPTTLBYPOPTHM_SmoothDer Derivative of Smoothed ADP Private Employment / Population
7072 NPPTTLBYPOPTHM_Log Log of ADP Private Employment / Population
7073 NPPTTLBYPOPTHM_mva200 ADP Private Employment / Population 200 Day MA
7074 NPPTTLBYPOPTHM_mva050 ADP Private Employment / Population 50 Day MA
7075 U6toU3_YoY U6RATE minums UNRATE Year over Year
7077 U6toU3_YoY5 U6RATE minums UNRATE 5 Year over 5 Year
7080 U6toU3_SmoothDer Derivative of Smoothed U6RATE minums UNRATE
7089 CHRISCMEHG1.by.PPIACO_SmoothDer Derivative of Smoothed Copper, $/lb, Normalized by commodities producer price index
7098 CHRISCMEHG1.by.CPIAUCSL_SmoothDer Derivative of Smoothed Copper, $/lb, Normalized by consumer price index
7105 DCOILBRENTEU.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7107 DCOILBRENTEU.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7109 DCOILBRENTEU.by.PPIACO_mva200 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 200 Day MA
7110 DCOILBRENTEU.by.PPIACO_mva050 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 50 Day MA
7114 DCOILWTICO.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7116 DCOILWTICO.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7117 DCOILWTICO.by.PPIACO_Log Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7118 DCOILWTICO.by.PPIACO_mva200 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 200 Day MA
7119 DCOILWTICO.by.PPIACO_mva050 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 50 Day MA
7123 LBMAGOLD.USD_PM.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gold, USD PM/Troy Ounce, Normalized by commodities producer price index
7125 LBMAGOLD.USD_PM.by.PPIACO_SmoothDer Derivative of Smoothed Gold, USD PM/Troy Ounce, Normalized by commodities producer price index
7128 LBMAGOLD.USD_PM.by.PPIACO_mva050 Gold, USD PM/Troy Ounce, Normalized by commodities producer price index 50 Day MA
7132 LBMAGOLD.USD_PM.by.CPIAUCSL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gold, USD/Troy OUnce, Normalized by consumer price index
7134 LBMAGOLD.USD_PM.by.CPIAUCSL_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by consumer price index
7137 LBMAGOLD.USD_PM.by.CPIAUCSL_mva050 Gold, USD/Troy OUnce, Normalized by consumer price index 50 Day MA
7141 LBMAGOLD.USD_PM.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gold, USD/Troy OUnce, Normalized by GDP
7143 LBMAGOLD.USD_PM.by.GDP_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by GDP
7146 LBMAGOLD.USD_PM.by.GDP_mva050 Gold, USD/Troy OUnce, Normalized by GDP 50 Day MA
7150 GSG.Close.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
7152 GSG.Close.by.GDPDEF_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by GDP def
7154 GSG.Close.by.GDPDEF_mva200 GSCI Commodity-Indexed Trust, Normalized by GDP def 200 Day MA
7155 GSG.Close.by.GDPDEF_mva050 GSCI Commodity-Indexed Trust, Normalized by GDP def 50 Day MA
7159 GSG.Close.by.GSPC.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
7161 GSG.Close.by.GSPC.Close_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
7163 GSG.Close.by.GSPC.Close_mva200 GSCI Commodity-Indexed Trust, Normalized by S&P 500 200 Day MA
7164 GSG.Close.by.GSPC.Close_mva050 GSCI Commodity-Indexed Trust, Normalized by S&P 500 50 Day MA
7172 GDPBYPOPTHM_mva200 GDP/Population 200 Day MA
7199 GSPC.CloseBYMDY.Close_mva200 GSPC by MDY 200 Day MA
7213 GSPC.DailySwing_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7215 GSPC.DailySwing_SmoothDer Derivative of Smoothed S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7216 GSPC.DailySwing_Log Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7240 HNFSUSNSA.minus.HSN1FNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Houses for sale - houses sold
7244 HNFSUSNSA.minus.HSN1FNSA_mva200 Houses for sale - houses sold 200 Day MA
7249 MSPUS.times.HOUST_Smooth Savitsky-Golay Smoothed (p=3, n=365) New privately owned units start times median price
7252 MSPUS.times.HOUST_Log Log of New privately owned units start times median price
7253 MSPUS.times.HOUST_mva200 New privately owned units start times median price 200 Day MA
7254 MSPUS.times.HOUST_mva050 New privately owned units start times median price 50 Day MA
7258 MSPUS.times.HNFSUSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New privately owned 1-family units for sale times median price
7261 MSPUS.times.HNFSUSNSA_Log Log of New privately owned 1-family units for sale times median price
7262 MSPUS.times.HNFSUSNSA_mva200 New privately owned 1-family units for sale times median price 200 Day MA
7263 MSPUS.times.HNFSUSNSA_mva050 New privately owned 1-family units for sale times median price 50 Day MA
7272 MULTPLSP500PERATIOMONTH_Mean S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-300, 300)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)
## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrial production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 12.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 150)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 60
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 242 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 10000)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Take a look at more recent trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 35000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).
## Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 2.5)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

# {r bond3monthlibor, echo=FALSE } # # datay <- "TB3MS" # datay_aux <- "USD1MTD156N" # ylim <- c(0, 12) # dtStart = as.Date('1985-01-01') # myPlot <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", # getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE) # myPlot <- myPlot + geom_line(data=df.data, aes_string(x="date", y=datay_aux, colour=shQuote(datay_aux)), na.rm = TRUE) # # myPlot # # Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(1.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

  • ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.
datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 105 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 190 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 596 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

  1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
  2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.